Serialized Form


Package gov.sandia.cognition.algorithm

Class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm extends AbstractIterativeAlgorithm implements Serializable

Serialized Fields

maxIterations

int maxIterations
Maximum number of iterations before stopping

Class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm extends AbstractCloneableSerializable implements Serializable

Serialized Fields

iteration

int iteration
Number of iterations the algorithm has executed.

Class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper extends AbstractIterativeAlgorithm implements Serializable

Serialization Methods

readResolve

protected Object readResolve()
This method is detected by the Java Serialization code and is called on deserialization. It allows the object to deal with transient values.

Serialized Fields

algorithm

AnytimeAlgorithm<ResultType> algorithm
Underlying algorithm to wrap.


Package gov.sandia.cognition.algorithm.event

Class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter extends AbstractIterativeAlgorithmListener implements Serializable

Serialized Fields

out

PrintStream out
The print stream to report performance to.


format

String format
The format for the performance report, passed to String.format.

Class gov.sandia.cognition.algorithm.event.IterationStartReporter extends AbstractIterativeAlgorithmListener implements Serializable

Serialized Fields

out

PrintStream out
The print stream to report performance to.


format

String format
The format for the performance report, passed to String.format.


Package gov.sandia.cognition.collection

Class gov.sandia.cognition.collection.AbstractMutableDoubleMap extends AbstractScalarMap<KeyType> implements Serializable

Serialized Fields

map

Map<K,V> map
Map backing that performs the storage.

Class gov.sandia.cognition.collection.AbstractScalarMap extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.collection.AbstractScalarMap.MapWrapper extends AbstractMap<KeyType,Double> implements Serializable

Class gov.sandia.cognition.collection.DefaultComparator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.collection.DefaultIndexer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

valueList

ArrayList<E> valueList
The list of values, which can be accessed by index.


valueToIndexMap

LinkedHashMap<K,V> valueToIndexMap
The mapping of values to their indices.

Class gov.sandia.cognition.collection.DefaultMultiCollection extends AbstractCollection<EntryType> implements Serializable

Serialized Fields

collections

List<E> collections
The set of collections that backs this collection.

Class gov.sandia.cognition.collection.DynamicArrayMap extends AbstractMap<Integer,ValueType> implements Serializable

Serialized Fields

array

Object[] array
The array underneath the mapping. Null values indicate an unassigned key.


numValues

int numValues
The number of non-null values in the array.

Class gov.sandia.cognition.collection.FiniteCapacityBuffer extends AbstractList<DataType> implements Serializable

Serialized Fields

data

Object[] data
Underlying data in the buffer


head

int head
Location of element 0


size

int size
Number of items in the list

Class gov.sandia.cognition.collection.IntegerSpan extends AbstractSet<Integer> implements Serializable

Serialized Fields

minValue

int minValue
Starting index, inclusive


maxValue

int maxValue
Stopping index, inclusive

Class gov.sandia.cognition.collection.MultiIterator extends Object implements Serializable

Serialized Fields

currentIterator

Iterator<E> currentIterator
The current iterator.


remainingIterators

LinkedList<E> remainingIterators
The iterators themselves.

Class gov.sandia.cognition.collection.NumberComparator extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.data.convert

Class gov.sandia.cognition.data.convert.AbstractDataConverter extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.data.convert.AbstractReverseCachedDataConverter extends AbstractReversibleDataConverter<InputType,OutputType> implements Serializable

Class gov.sandia.cognition.data.convert.AbstractReversibleDataConverter extends AbstractDataConverter<InputType,OutputType> implements Serializable

Class gov.sandia.cognition.data.convert.IdentityDataConverter extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.data.convert.ObjectToStringConverter extends AbstractDataConverter<Object,String> implements Serializable


Package gov.sandia.cognition.data.convert.number

Class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter extends AbstractReverseCachedDataConverter<Boolean,Number,DefaultBooleanToNumberConverter.Reverse> implements Serializable

Serialized Fields

trueValue

Number trueValue
The number to use to represent a true value.


falseValue

Number falseValue
The number to use to represent a false value.


nullValue

Number nullValue
The number to use to represent a null value.

Class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter.Reverse extends AbstractReversibleDataConverter<Number,Boolean> implements Serializable

Class gov.sandia.cognition.data.convert.number.StringToDoubleConverter extends AbstractReverseCachedDataConverter<String,Double,ObjectToStringConverter> implements Serializable

Class gov.sandia.cognition.data.convert.number.StringToIntegerConverter extends AbstractReverseCachedDataConverter<String,Integer,ObjectToStringConverter> implements Serializable


Package gov.sandia.cognition.data.convert.vector

Class gov.sandia.cognition.data.convert.vector.AbstractToVectorEncoder extends AbstractDataConverter<InputType,Vector> implements Serializable

Serialized Fields

vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The vector factory to use to create new vectors.

Class gov.sandia.cognition.data.convert.vector.NumberConverterToVectorAdapter extends AbstractToVectorEncoder<InputType> implements Serializable

Serialized Fields

converter

DataConverter<InputType,OutputType> converter
The converter to adapt for use with Vectors.

Class gov.sandia.cognition.data.convert.vector.NumberToVectorEncoder extends AbstractToVectorEncoder<Number> implements Serializable

Class gov.sandia.cognition.data.convert.vector.UniqueBooleanVectorEncoder extends AbstractToVectorEncoder<InputType> implements Serializable

Serialized Fields

values

List<E> values
The set of possible unique values.


booleanConverter

DataToVectorEncoder<InputType> booleanConverter
The boolean encoder for the equality comparison between each of the possible values and a given input.


Package gov.sandia.cognition.evaluator

Class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

state

CloneableSerializable state
Current state object.

Class gov.sandia.cognition.evaluator.CompositeEvaluatorList extends AbstractCloneableSerializable implements Serializable

Serialized Fields

evaluators

ArrayList<E> evaluators
The list of evaluators to compose together.

Class gov.sandia.cognition.evaluator.CompositeEvaluatorPair extends DefaultPair<Evaluator<? super InputType,? extends IntermediateType>,Evaluator<? super IntermediateType,? extends OutputType>> implements Serializable

Class gov.sandia.cognition.evaluator.CompositeEvaluatorTriple extends DefaultTriple<Evaluator<? super InputType,? extends FirstIntermediateType>,Evaluator<? super FirstIntermediateType,? extends SecondIntermediateType>,Evaluator<? super SecondIntermediateType,? extends OutputType>> implements Serializable

Class gov.sandia.cognition.evaluator.ForwardReverseEvaluatorPair extends AbstractCloneableSerializable implements Serializable

Serialized Fields

forward

Evaluator<InputType,OutputType> forward
The forward evaluator from input type to output type.


reverse

Evaluator<InputType,OutputType> reverse
The reverse evaluator from output type to input type.

Class gov.sandia.cognition.evaluator.IdentityEvaluator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.evaluator.ValueClamper extends AbstractCloneableSerializable implements Serializable

Serialized Fields

minimum

Comparable<T> minimum
The minimum possible value. May be null to not clamp to the minimum.


maximum

Comparable<T> maximum
The maximum possible value. May be null to not clamp to the maximum.

Class gov.sandia.cognition.evaluator.ValueMapper extends AbstractCloneableSerializable implements Serializable

Serialized Fields

valueMap

Map<K,V> valueMap
The map to use to map input values to output values.


Package gov.sandia.cognition.factory

Class gov.sandia.cognition.factory.DefaultFactory extends AbstractCloneableSerializable implements Serializable

Serialized Fields

createdClass

Class<T> createdClass
The class whose default constructor is used to create new objects.

Class gov.sandia.cognition.factory.PrototypeFactory extends AbstractCloneableSerializable implements Serializable

Serialized Fields

prototype

CloneableSerializable prototype
The prototype to create clones from.


Package gov.sandia.cognition.framework

Class gov.sandia.cognition.framework.AbstractCognitiveModel extends Object implements Serializable

Class gov.sandia.cognition.framework.AbstractCognitiveModelFactory extends Object implements Serializable

Serialized Fields

moduleFactories

ArrayList<E> moduleFactories
The list of CognitiveModuleFactories to use for the model.

Class gov.sandia.cognition.framework.AbstractSemanticIdentifier extends Object implements Serializable

Class gov.sandia.cognition.framework.CognitiveModelStateChangeEvent extends EventObject implements Serializable

Serialized Fields

model

CognitiveModel model
The model whose state has changed.


state

CognitiveModelState state
The new state of the model.

Class gov.sandia.cognition.framework.DefaultCogxel extends AbstractCloneableSerializable implements Serializable

Serialized Fields

semanticIdentifier

SemanticIdentifier semanticIdentifier
The SemanticIdentifier that identifies the Cogxel.


activation

double activation
The current activation of the Cogxel.

Class gov.sandia.cognition.framework.DefaultCogxelFactory extends Object implements Serializable

Class gov.sandia.cognition.framework.DefaultSemanticIdentifier extends AbstractSemanticIdentifier implements Serializable

Serialized Fields

label

SemanticLabel label
The SemanticLabel that is identified.


identifier

int identifier
The unique identifier for the semantic label.

Class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap extends AbstractCloneableSerializable implements Serializable

Serialized Fields

identifierCounter

int identifierCounter
The counter of identifiers, which ensures that each one is unique.


mapping

LinkedHashMap<K,V> mapping
The mapping of semantic labels to semantic identifiers.

Class gov.sandia.cognition.framework.DefaultSemanticLabel extends Object implements Serializable

Serialized Fields

label

String label
The String label.

Class gov.sandia.cognition.framework.DefaultSemanticNetwork extends Object implements Serializable

Serialized Fields

labelNodeMap

TreeMap<K,V> labelNodeMap
The mapping of labels onto nodes in the network.

Class gov.sandia.cognition.framework.SemanticIdentifierMapEvent extends EventObject implements Serializable

Serialized Fields

map

SemanticIdentifierMap map
The map that the event happened in.


eventType

SemanticIdentifierMapEventType eventType
The type of event that this is.


identifier

SemanticIdentifier identifier
The SemanticIdentifier causing the event.


Package gov.sandia.cognition.framework.concurrent

Class gov.sandia.cognition.framework.concurrent.AbstractConcurrentCognitiveModule extends Object implements Serializable

Class gov.sandia.cognition.framework.concurrent.MultithreadedCognitiveModel extends AbstractCognitiveModelLite implements Serializable

Serialized Fields

modules

ConcurrentCognitiveModule[] modules
The CognitiveModules that are part of this model.


fixedThreadPool

ExecutorService fixedThreadPool
A thread pool for managing concurrent evaluation of modules

Class gov.sandia.cognition.framework.concurrent.MultithreadedCognitiveModelFactory extends AbstractCognitiveModelFactory implements Serializable

Serialized Fields

numThreadsInPool

int numThreadsInPool
Number of threads to use in the thread pool


Package gov.sandia.cognition.framework.learning

Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule extends AbstractConcurrentCognitiveModule implements Serializable

Serialized Fields

name

String name
Name to assign to the module


settings

EvaluatorBasedCognitiveModuleSettings<InputType,OutputType> settings
The module settings.


input

Object input
A place to temporarily store the input read in by a call to readState; this temporary store is blown away as soon as it used by evaluate, because we NEVER retain state interally across module update cycles


output

Object output
A place to temporarily store the output generated by a call to evaluate; this temporary store is blown away as soon as it used by evaluate, because we NEVER retain state interally across module update cycles

Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactory extends Object implements Serializable

Serialized Fields

settings

EvaluatorBasedCognitiveModuleSettings<InputType,OutputType> settings
The settings for the module.


name

String name
Human-readable name of the module

Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner extends Object implements Serializable

Serialized Fields

learner

BatchLearner<DataType,ResultType> learner
The learner to use to learn the evaluator


inputConverter

CogxelConverter<DataType> inputConverter
The CogxelConverter used to convert from a CogxelState to InputType


outputConverter

CogxelConverter<DataType> outputConverter
The CogxelConverter used to convert OutputType to a CogxelState.


learningDataConverter

CogxelConverter<DataType> learningDataConverter
The CogxelConverter used to convert from a CogxelState to LearningDataType.


name

String name
Human-readable name for this module

Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleSettings extends Object implements Serializable

Serialized Fields

evaluator

Evaluator<InputType,OutputType> evaluator
The evaluator to be used by the module.


inputConverter

CogxelConverter<DataType> inputConverter
The CogxelConverter used to convert from a CogxelState to InputType.


outputConverter

CogxelConverter<DataType> outputConverter
The CogxelConverter used to convert OutputType to a CogxelState.

Class gov.sandia.cognition.framework.learning.StatefulEvaluatorBasedCognitiveModule extends EvaluatorBasedCognitiveModule<InputType,OutputType> implements Serializable

Serialized Fields

stateWrapper

CognitiveModuleStateWrapper stateWrapper
A place to store the wrapper for the CognitiveModuleState that is initialized by readState and later used by writeState


Package gov.sandia.cognition.framework.learning.converter

Class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter extends AbstractCloneableSerializable implements Serializable

Serialized Fields

semanticIdentifierMap

SemanticIdentifierMap semanticIdentifierMap
The SemanticIdentifierMap for the converter.

Class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter extends AbstractCogxelConverter<PairType extends Pair<FirstType,SecondType>> implements Serializable

Serialized Fields

firstConverter

CogxelConverter<DataType> firstConverter
The CogxelConverter for the first element of the pair.


secondConverter

CogxelConverter<DataType> secondConverter
The CogxelConverter for the second element of the pair.

Class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter extends AbstractCogxelConverter<Boolean> implements Serializable

Serialized Fields

label

SemanticLabel label
The label of the Cogxel to convert.


identifier

SemanticIdentifier identifier
The semantic identifier of the Cogxel to convert.


cogxelFactory

CogxelFactory cogxelFactory
The CogxelFactory to use.

Class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter extends Object implements Serializable

Serialized Fields

label

SemanticLabel label
The label of the Cogxel to convert.


identifier

SemanticIdentifier identifier
The semantic identifier of the Cogxel to convert.


semanticIdentifierMap

SemanticIdentifierMap semanticIdentifierMap
The SemanticIdentifierMap for the converter.


cogxelFactory

CogxelFactory cogxelFactory
The CogxelFactory to use.

Class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter extends AbstractCogxelPairConverter<InputType,OutputType,InputOutputPair<InputType,OutputType>> implements Serializable

Class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter extends Object implements Serializable

Serialized Fields

columnConverters

ArrayList<E> columnConverters
Collection CogxelVectorConverters that convert the columns of the matrix


semanticIdentifierMap

SemanticIdentifierMap semanticIdentifierMap
SemanticIdentifierMap for the converter

Class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter extends AbstractCogxelPairConverter<TargetType,EstimateType,TargetEstimatePair<TargetType,EstimateType>> implements Serializable

Class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter extends Object implements Serializable

Serialized Fields

cogxelVectorConverters

Collection<E> cogxelVectorConverters
Collection of CogxelVectorConverters that do the heavy lifting

Class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter extends DefaultVectorFactoryContainer implements Serializable

Serialized Fields

labels

ArrayList<E> labels
The labels for each of the elements in the vector.


semanticIdentifierMap

SemanticIdentifierMap semanticIdentifierMap
The current SemanticIdentifierMap.


identifiers

ArrayList<E> identifiers
The list of SemanticIdentifiers, whose positions correspond to positions in the vector.


identifierToIndexMap

HashMap<K,V> identifierToIndexMap
The mapping of SemanticIdentifiers to vector indices.


cogxelFactory

CogxelFactory cogxelFactory
The CogxelFactory to use.

Class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter extends Object implements Serializable

Serialized Fields

pairConverter

CogxelInputOutputPairConverter<InputType,OutputType> pairConverter
Creates the underlying InputOutputPair


weightConverter

CogxelConverter<DataType> weightConverter
Adds the weight to the InputOutputPair


Package gov.sandia.cognition.framework.lite

Class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite extends AbstractCognitiveModel implements Serializable

Serialized Fields

numModules

int numModules
The number of modules.


semanticIdentifierMap

DefaultSemanticIdentifierMap semanticIdentifierMap
The semantic identifier database.


state

CognitiveModelLiteState state
The current state of the model.

Class gov.sandia.cognition.framework.lite.AbstractSemanticMemoryLite extends Object implements Serializable

Serialized Fields

semanticIdentifierMap

SemanticIdentifierMap semanticIdentifierMap
The mapping of semantic labels to semantic identifiers.


recognizer

PatternRecognizerLite recognizer
The PatternRecognizerLite that is used.


outputIdentifiers

ArrayList<E> outputIdentifiers
The mapping of output vector entries to identifiers.

Class gov.sandia.cognition.framework.lite.ArrayBasedCognitiveModelInput extends Object implements Serializable

Serialized Fields

identifiers

SemanticIdentifier[] identifiers
The identifiers to use as inputs.


values

double[] values
The activation values of the inputs.

Class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule extends AbstractConcurrentCognitiveModule implements Serializable

Serialized Fields

semanticIdentifierMap

SemanticIdentifierMap semanticIdentifierMap
The semantic identifier map. Currently unused, but provided because there may be a need to support SemanticLabels instead of identifiers later on.


cogxelFactory

CogxelFactory cogxelFactory
The factory for creating Cogxels for perception.


input

ArrayBasedCognitiveModelInput input
A place to temporarily store the input read in by a call to readState; this temporary store is blown away as soon as it used by writeState, because we NEVER retain state interally across module update cycles

Class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModuleFactory extends Object implements Serializable

Serialized Fields

cogxelFactory

CogxelFactory cogxelFactory
The CogxelFactory for the module to use in creating Cogxels.

Class gov.sandia.cognition.framework.lite.BooleanActivatableCogxel extends DefaultCogxel implements Serializable

Serialized Fields

activated

boolean activated
A boolean indicating whether the cogxel is activated.

Class gov.sandia.cognition.framework.lite.BooleanActivatableCogxelFactory extends Object implements Serializable

Class gov.sandia.cognition.framework.lite.CognitiveModelLite extends AbstractCognitiveModelLite implements Serializable

Serialized Fields

modules

CognitiveModule[] modules
The CognitiveModules that are part of this model.

Class gov.sandia.cognition.framework.lite.CognitiveModelLiteFactory extends AbstractCognitiveModelFactory implements Serializable

Class gov.sandia.cognition.framework.lite.CognitiveModelLiteState extends AbstractCloneableSerializable implements Serializable

Serialized Fields

initialized

boolean initialized
A flag indicating if the state has been initialized or not.


input

CognitiveModelInput input
The input to the model.


cogxels

CogxelStateLite cogxels
The state of the Cogxels.


moduleStatesArray

CognitiveModuleState[] moduleStatesArray
The states of the modules.

Class gov.sandia.cognition.framework.lite.CognitiveModuleStateWrapper extends AbstractCloneableSerializable implements Serializable

Serialized Fields

internalState

CloneableSerializable internalState
The internal state object that is wrapped.

Class gov.sandia.cognition.framework.lite.CogxelStateLite extends AbstractCloneableSerializable implements Serializable

Serialized Fields

cogxels

DynamicArrayMap<ValueType> cogxels
The underlying mapping of identifiers to cogxels.

Class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLite extends AbstractSemanticMemoryLite implements Serializable

Serialized Fields

mutableRecognizer

MutablePatternRecognizerLite mutableRecognizer
The mutable pattern recognizer to modify.


identifierToInputIndexMap

HashMap<K,V> identifierToInputIndexMap
The mapping of identifier number to input vector index number.


nodeSet

HashSet<E> nodeSet
The set of nodes used by the memory.

Class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLiteFactory extends Object implements Serializable

Serialized Fields

recognizer

MutablePatternRecognizerLite recognizer
The module settings.

Class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLite extends AbstractSemanticMemoryLite implements Serializable

Serialized Fields

sharedSettings

SharedSemanticMemoryLiteSettings sharedSettings
The shared settings for this semantic memory.


minIdentifier

int minIdentifier
The minimum identifier number.


maxIdentifier

int maxIdentifier
The maximum identifier number.


identifierToInputIndexMap

int[] identifierToInputIndexMap
The mapping of input indentifier to input index.

Class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteFactory extends AbstractCloneableSerializable implements Serializable

Serialized Fields

settings

SharedSemanticMemoryLiteSettings settings
The shared settings between the modules.

Class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteSettings extends AbstractCloneableSerializable implements Serializable

Serialized Fields

recognizer

PatternRecognizerLite recognizer
The recognizer to use in the memory.

Class gov.sandia.cognition.framework.lite.SimplePatternRecognizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

nodes

ArrayList<E> nodes
The nodes in the recognition network, sorted by how they are to appear in the vector.


nodeToIDMap

HashMap<K,V> nodeToIDMap
The mapping of semantic labels to their index in the vector.


matrix

Matrix matrix
The matrix underlying the pattern recognizer.


nodesChangedSinceLastUpdate

boolean nodesChangedSinceLastUpdate
True if the set of nodes has changed since the last update.

Class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState extends AbstractCloneableSerializable implements Serializable

Serialized Fields

labels

ArrayList<E> labels
The array of semantic labels that the state vector has. This is stored as a private copy in the state object because the module can have labels added or removed. If that happens then the module will need to update the state based on the new labels.


stateVector

Vector stateVector
The state vector.

Class gov.sandia.cognition.framework.lite.VectorBasedCognitiveModelInput extends AbstractCloneableSerializable implements Serializable

Serialized Fields

identifiers

SemanticIdentifier[] identifiers
Identifiers to use associate with the inputs


values

Vector values
Activation values of the inputs

Class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModule extends Object implements Serializable

Serialized Fields

cogxelFactory

CogxelFactory cogxelFactory
Factory for creating Cogxels for perception

Class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModuleFactory extends Object implements Serializable

Serialized Fields

cogxelFactory

CogxelFactory cogxelFactory
CogxelFactory for the module to use in creating Cogxels


Package gov.sandia.cognition.io

Class gov.sandia.cognition.io.CSVParseException extends Exception implements Serializable


Package gov.sandia.cognition.io.serialization

Class gov.sandia.cognition.io.serialization.AbstractFileSerializationHandler extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.io.serialization.AbstractStreamSerializationHandler extends AbstractFileSerializationHandler<SerializedType> implements Serializable

Class gov.sandia.cognition.io.serialization.AbstractTextSerializationHandler extends AbstractStreamSerializationHandler<SerializedType> implements Serializable

Serialization Methods

readObject

public Object readObject(InputStream stream)
                  throws IOException,
                         ClassNotFoundException
Throws:
IOException - If there is an i/o error.
ClassNotFoundException - If a class cannot be found.

writeObject

public void writeObject(OutputStream stream,
                        SerializedType object)
                 throws IOException
Throws:
IOException - If there is an i/o error.

Class gov.sandia.cognition.io.serialization.GZIPSerializationHandler extends AbstractStreamSerializationHandler<SerializedType> implements Serializable

Serialization Methods

readObject

public Object readObject(InputStream stream)
                  throws IOException,
                         ClassNotFoundException
Throws:
IOException - If there is an i/o error.
ClassNotFoundException - If a class cannot be found.

writeObject

public void writeObject(OutputStream stream,
                        SerializedType object)
                 throws IOException
Throws:
IOException - If there is an i/o error.
Serialized Fields

baseHandler

StreamSerializationHandler<SerializedType> baseHandler
The base handler that is being wrapped in a GZip.

Class gov.sandia.cognition.io.serialization.JavaDefaultBinarySerializationHandler extends AbstractStreamSerializationHandler<Serializable> implements Serializable

Serialization Methods

readObject

public Object readObject(InputStream stream)
                  throws IOException,
                         ClassNotFoundException
Throws:
IOException - If there is an i/o error.
ClassNotFoundException - If a class cannot be found.

writeObject

public void writeObject(OutputStream stream,
                        Serializable object)
                 throws IOException
Throws:
IOException - If there is an i/o error.

Class gov.sandia.cognition.io.serialization.XStreamSerializationHandler extends AbstractTextSerializationHandler<Serializable> implements Serializable

Serialization Methods

readObject

public Object readObject(Reader reader)
                  throws IOException
Throws:
IOException - If there is an i/o error.

writeObject

public void writeObject(Writer writer,
                        Serializable object)
                 throws IOException
Throws:
IOException - If there is an i/o error.

Package gov.sandia.cognition.learning.algorithm

Class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner extends AbstractAnytimeAlgorithm<ResultType> implements Serializable

Serialized Fields

keepGoing

boolean keepGoing
Indicates whether or not the learner should make another step.


data

Object data
The data to learn from.

Class gov.sandia.cognition.learning.algorithm.AbstractAnytimeSupervisedBatchLearner extends AbstractAnytimeBatchLearner<Collection<? extends InputOutputPair<? extends InputType,OutputType>>,ResultType extends Evaluator<? super InputType,? extends OutputType>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.AbstractBatchLearnerContainer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

learner

BatchLearner<DataType,ResultType> learner
The wrapped learner.

Class gov.sandia.cognition.learning.algorithm.AbstractSupervisedBatchAndIncrementalLearner extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType extends Evaluator<? super InputType,? extends OutputType>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair extends AbstractCloneableSerializable implements Serializable

Serialized Fields

firstLearner

BatchLearner<DataType,ResultType> firstLearner
The first learner that is trained on the input data.


secondLearner

BatchLearner<DataType,ResultType> secondLearner
The second learner that is trained on the output of the evaluator created by the first learner.

Class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner extends AbstractBatchLearnerContainer<BatchLearner<? super Collection<? extends InputOutputPair<? extends TransformedInputType,TransformedOutputType>>,? extends Evaluator<? super TransformedInputType,? extends TransformedOutputType>>> implements Serializable

Serialized Fields

inputLearner

BatchLearner<DataType,ResultType> inputLearner
The unsupervised learning algorithm for creating the input transformation.


outputLearner

BatchLearner<DataType,ResultType> outputLearner
The unsupervised learning algorithm for creating the output transformation, which must be reversible for evaluation.

Class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner extends AbstractBatchLearnerContainer<BatchLearner<? super Collection<? extends InputOutputPair<? extends DataType,DataType>>,? extends LearnedType>> implements Serializable

Serialized Fields

predictionHorizon

int predictionHorizon
The prediction horizon, which is the number of samples in the future to try to learn to predict. It must be a positive number.

Class gov.sandia.cognition.learning.algorithm.TimeSeriesPredictionLearner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

predictionHorizon

int predictionHorizon
Number of samples into the future to predict.


supervisedLearner

SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> supervisedLearner
Learning algorithm that does the heavy lifting.


Package gov.sandia.cognition.learning.algorithm.annealing

Class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer extends AbstractAnytimeBatchLearner<CostParametersType,AnnealedType> implements Serializable

Serialized Fields

cost

CostFunction<EvaluatedType,CostParametersType> cost
The cost function to minimize.


perturber

Perturber<PerturbedType> perturber
The perturbing function to use to perturb the objects.


temperature

double temperature
The current temperature.


maxIterationsWithoutImprovement

int maxIterationsWithoutImprovement
The maximum number of iterations to go without improvement before stopping.


iterationsWithoutImprovement

int iterationsWithoutImprovement
The number of iterations since the last improvement.


coolingFactor

double coolingFactor
The cooling factor applied at each step.


random

Random random
The random number generator to use.


bestSoFar

Object bestSoFar
The best state found so far.


bestSoFarScore

double bestSoFarScore
The score for the best state found so far.


current

Object current
The current state.


currentScore

double currentScore
The score of the current state.

Class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber extends AbstractRandomized implements Serializable

Serialized Fields

covarianceSqrt

Matrix covarianceSqrt
The covariance square root matrix to use while perturbing.


Package gov.sandia.cognition.learning.algorithm.baseline

Class gov.sandia.cognition.learning.algorithm.baseline.ConstantLearner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

value

Object value
The result of learning.

Class gov.sandia.cognition.learning.algorithm.baseline.IdentityLearner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.baseline.MeanLearner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.baseline.MostFrequentLearner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.baseline.WeightedMeanLearner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.baseline.WeightedMostFrequentLearner extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.algorithm.bayes

Class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

conditionalProbabilities

Map<K,V> conditionalProbabilities
Class conditional probability table.


priorProbabilities

DefaultDataDistribution<KeyType> priorProbabilities
Table of category priors.


inputDimensionality

int inputDimensionality
Assumed dimensionality of the inputs.

Class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer.Learner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

priors

DataDistribution<DataType> priors
The prior distribution for the categorizer.


conditionals

Map<K,V> conditionals
The mapping of category to the conditional distribution for the category with one probability density function for each dimension.

Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.BatchGaussianLearner extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.Learner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

distributionEstimator

DistributionEstimator<ObservationType,DistributionType extends Distribution<? extends ObservationType>> distributionEstimator
The distributionLearner for the distribution of each dimension of each category.

Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,VectorNaiveBayesCategorizer<CategoryType,DistributionType extends UnivariateProbabilityDensityFunction>> implements Serializable

Serialized Fields

distributionLearner

IncrementalLearner<DataType,ResultType> distributionLearner
The incremental learner for the distribution used to represent each dimension. By the generic, it must learn a univariate probability density function.


Package gov.sandia.cognition.learning.algorithm.clustering

Class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation extends AbstractAnytimeBatchLearner<Collection<? extends DataType>,Collection<CentroidCluster<DataType>>> implements Serializable

Serialized Fields

divergence

DivergenceFunction<FirstType,SecondType> divergence
The divergence function to use.


selfDivergence

double selfDivergence
The value to use for self-divergence. Controls the number of clusters created.


dampingFactor

double dampingFactor
The damping factor (lambda). It must be between 0.0 and 1.0.


oneMinusDampingFactor

double oneMinusDampingFactor
The cached value of one minus the damping factor.


examples

ArrayList<E> examples
The examples.


similarities

double[][] similarities
The array of example-example similarities.


responsibilities

double[][] responsibilities
The array of example-example responsibilities.


availabilities

double[][] availabilities
The array of example-example availabilities.


assignments

int[] assignments
The assignments of each example to an exemplar (cluster).


changedCount

int changedCount
The number of examples that have changed assignments in the last iteration.


clusters

HashMap<K,V> clusters
The clusters that have been found so far. It is a sparse mapping since we expect there to be few clusters.

Class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer extends AbstractAnytimeBatchLearner<Collection<? extends DataType>,Collection<ClusterType extends Cluster<DataType>>> implements Serializable

Serialized Fields

divergenceFunction

ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> divergenceFunction
The divergence function used to find the distance between two clusters.


creator

ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
The merger used to merge two clusters into one element.


minNumClusters

int minNumClusters
The minimum number of clusters allowed.


maxMinDistance

double maxMinDistance
The maximum minimum distance between clusters allowed.


clusters

ArrayList<E> clusters
The current set of clusters.


clustersHierarchy

ArrayList<E> clustersHierarchy
The current set of hierarchical clusters.

Class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode extends BinaryClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> implements Serializable

Serialized Fields

childrenDivergence

double childrenDivergence
The divergence between the two children, if they exist.

Class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering extends AnytimeAlgorithmWrapper<Collection<GaussianCluster>,DirichletProcessMixtureModel<Vector>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer extends AbstractAnytimeBatchLearner<Collection<? extends DataType>,Collection<ClusterType extends Cluster<DataType>>> implements Serializable

Serialized Fields

numRequestedClusters

int numRequestedClusters
The number of clusters requested.


initializer

FixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> initializer
The initializer for the algorithm.


divergenceFunction

ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> divergenceFunction
The divergence function between cluster being used.


creator

ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
The cluster creator for creating clusters.


clusters

ArrayList<E> clusters
The current set of clusters.


assignments

int[] assignments
The current assignments of elements to clusters.


clusterCounts

int[] clusterCounts
The current number of elements assigned to each cluster.


numChanged

int numChanged
Returns the number of samples that changed assignment between iterations

Class gov.sandia.cognition.learning.algorithm.clustering.KMeansClustererWithRemoval extends KMeansClusterer<DataType,ClusterType extends Cluster<DataType>> implements Serializable

Serialized Fields

removalThreshold

double removalThreshold
fraction of the expected number of data points assigned to a cluster below which the cluster will be removed. (Suppose there are 1000 datapoint, 10 clusters, and removalThreshold=0.1. A cluster may be removed only if is has membership less than 0.1*1000/10= 10 elements assigned to it.)

Class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory extends AbstractRandomized implements Serializable

Serialized Fields

numClusters

int numClusters
Number of clusters to use. Must be positive.

Class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer extends KMeansClusterer<DataType,CentroidCluster<DataType>> implements Serializable

Serialized Fields

metric

Metric<EvaluatedType> metric
The metric being used.


lowerBounds

double[][] lowerBounds
The lower bounds on the distances to the clusters.


upperBounds

double[] upperBounds
The upper bounds on the distance to the current assigned cluster.


clusterDistances

double[][] clusterDistances
The distances between clusters.

Class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer extends KMeansClusterer<DataType,ClusterType extends Cluster<DataType>> implements Serializable

Serialized Fields

assignmentTasks

ArrayList<E> assignmentTasks
Parallel tasks that assign the data points to clusters


clusterCreatorTask

ArrayList<E> clusterCreatorTask
Parallel tasks that creates clusters from the assigned data points


assignmentList

Collection<E> assignmentList
ArrayList of assignments from the subtasks


newAssignments

int[] newAssignments
Array of new assignments

Class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer extends AbstractAnytimeBatchLearner<Collection<? extends DataType>,Collection<ClusterType extends Cluster<DataType>>> implements Serializable

Serialized Fields

divergenceFunction

ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> divergenceFunction
The divergence function used to find the distance between two clusters.


creator

IncrementalClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
The merger used to merge two clusters into one element.


minClusterSize

int minClusterSize
The minimum number of elements per cluster allowed.


maxCriterionDecrease

double maxCriterionDecrease
The maximum decrease in training criterion allowed.


random

Random random
The source of randomness used during initial partitioning.


Package gov.sandia.cognition.learning.algorithm.clustering.cluster

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster extends DefaultCluster<ClusterType> implements Serializable

Serialized Fields

centroid

Object centroid
The center of the cluster.

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster extends AbstractCloneableSerializable implements Serializable

Serialized Fields

index

int index
The index of the cluster in the collection of clusters.


members

ArrayList<E> members
The members of the cluster.

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultClusterCreator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultIncrementalClusterCreator extends DefaultClusterCreator<DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianCluster extends DefaultCluster<Vector> implements Serializable

Serialized Fields

gaussian

MultivariateGaussian.PDF gaussian
The Gaussian distribution that the cluster represents.

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianClusterCreator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

defaultCovariance

double defaultCovariance
amount to add to the diagonals of the covariance matrix, typically on the order of 1e-4.

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.MedoidClusterCreator extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanCentroidClusterCreator extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.algorithm.clustering.divergence

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.AbstractClusterToClusterDivergenceFunction extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.CentroidClusterDivergenceFunction extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCentroidDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<CentroidCluster<DataType>,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCompleteLinkDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterMeanLinkDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterSingleLinkDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.divergence.GaussianClusterDivergenceFunction extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.algorithm.clustering.hierarchy

Class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.AbstractClusterHierarchyNode extends AbstractCloneableSerializable implements Serializable

Serialized Fields

cluster

Cluster<ClusterType> cluster
The cluster associated with the node.

Class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.BinaryClusterHierarchyNode extends AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> implements Serializable

Serialized Fields

firstChild

ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> firstChild
The first child node.


secondChild

ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> secondChild
The second child node.

Class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode extends AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> implements Serializable

Serialized Fields

children

List<E> children
The list of children.


Package gov.sandia.cognition.learning.algorithm.clustering.initializer

Class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable

Serialized Fields

creator

ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
The ClusterCreator to create the initial clusters from.


random

Random random
The random number generator to use.

Class gov.sandia.cognition.learning.algorithm.clustering.initializer.DistanceSamplingClusterInitializer extends AbstractMinDistanceFixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.initializer.GreedyClusterInitializer extends AbstractMinDistanceFixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer extends AbstractRandomized implements Serializable

Serialized Fields

defaultCovariance

double defaultCovariance
default diagonal covariance scaling factor


randomRange

double randomRange
range of the neighborhood from which to place the cluster


Package gov.sandia.cognition.learning.algorithm.confidence

Class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,Boolean,DefaultConfidenceWeightedBinaryCategorizer> implements Serializable

Serialized Fields

r

double r
The r parameter that controls regularization weight. Must be positive.

Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,Boolean,DiagonalConfidenceWeightedBinaryCategorizer> implements Serializable

Serialized Fields

confidence

double confidence
The confidence to use for updating. Must be in [0.5, 1]. Called eta in the paper.


defaultVariance

double defaultVariance
The default variance, which the diagonal of the covariance matrix is initialized to. Must be positive. Called a in the paper.


phi

double phi
Phi is the standard score computed from the confidence.


psi

double psi
Psi is the cached value 1 + phi^2 / 2.


epsilon

double epsilon
Epsilon is the cached value 1 + phi^2.

Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviationProject extends ConfidenceWeightedDiagonalDeviation implements Serializable

Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,Boolean,DiagonalConfidenceWeightedBinaryCategorizer> implements Serializable

Serialized Fields

confidence

double confidence
The confidence to use for updating. Must be in [0, 1]. Called eta in the paper.


defaultVariance

double defaultVariance
The default variance, which the diagonal of the covariance matrix is initialized to. Must be positive. Called a in the paper.


phi

double phi
Phi is the standard score computed from the confidence.

Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVarianceProject extends ConfidenceWeightedDiagonalVariance implements Serializable


Package gov.sandia.cognition.learning.algorithm.ensemble

Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner extends AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,EnsembleType extends Evaluator<? super InputType,? extends OutputType>> implements Serializable

Serialized Fields

learner

BatchLearner<DataType,ResultType> learner
The learner to use to create the categorizer for each iteration.


percentToSample

double percentToSample
The percentage of the data to sample with replacement on each iteration. Must be positive. Represented as a floating point number with 1.0 meaning 100%.


random

Random random
The random number generator to use.

Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble extends AbstractCloneableSerializable implements Serializable

Serialized Fields

members

List<E> members
The members of the ensemble.

Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble extends AbstractCloneableSerializable implements Serializable

Serialized Fields

members

List<E> members
The members of the ensemble.

Class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost extends AbstractAnytimeSupervisedBatchLearner<InputType,Boolean,WeightedBinaryEnsemble<InputType,Evaluator<? super InputType,? extends Boolean>>> implements Serializable

Serialized Fields

weakLearner

BatchLearner<DataType,ResultType> weakLearner
The "weak learner" that must learn from the weighted input-output pairs on each iteration.

Class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble extends AbstractUnweightedEnsemble<MemberType extends Evaluator<? super InputType,? extends Number>> implements Serializable

Serialized Fields

bias

double bias
The initial offset value that the ensemble outputs are added to.

Class gov.sandia.cognition.learning.algorithm.ensemble.AveragingEnsemble extends AbstractUnweightedEnsemble<MemberType extends Evaluator<? super InputType,? extends Number>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner extends AbstractBaggingLearner<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.ensemble.BaggingRegressionLearner extends AbstractBaggingLearner<InputType,Double,Evaluator<? super InputType,? extends Number>,AveragingEnsemble<InputType,Evaluator<? super InputType,? extends Number>>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.ensemble.BinaryBaggingLearner extends AbstractBaggingLearner<InputType,Boolean,Evaluator<? super InputType,? extends Boolean>,WeightedBinaryEnsemble<InputType,Evaluator<? super InputType,? extends Boolean>>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.ensemble.BinaryCategorizerSelector extends AbstractCloneableSerializable implements Serializable

Serialized Fields

categorizers

Collection<E> categorizers
The collection of categorizers to evaluate and select from.

Class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner extends BaggingCategorizerLearner<InputType,CategoryType> implements Serializable

Serialized Fields

categoryList

ArrayList<E> categoryList
The list of categories.


dataPerCategory

HashMap<K,V> dataPerCategory
The mapping of categories to indices of examples belonging to the category.

Class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedIVotingLearner extends IVotingCategorizerLearner<InputType,CategoryType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner extends AbstractAnytimeSupervisedBatchLearner<InputType,CategoryType,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>> implements Serializable

Serialized Fields

learner

BatchLearner<DataType,ResultType> learner
The learner used to produce each ensemble member.


percentToSample

double percentToSample
The percent to sample on each iteration.


proportionIncorrectInSample

double proportionIncorrectInSample
The proportion of incorrect examples in each sample. Must be between 0.0 and 1.0 (inclusive).


voteOutOfBagOnly

boolean voteOutOfBagOnly
Controls whether or not an ensemble member can vote on items it was trained on during learning. By default, the ensemble member can only vote on out-of-bag values.


counterFactory

Factory<CreatedType> counterFactory
Factory for counting votes.


random

Random random
The random number generator to use.

Class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria extends AbstractIterativeAlgorithmListener implements Serializable

Serialized Fields

smoothingWindowSize

int smoothingWindowSize
The size of window of data to look at to determine if learning has hit a minimum.

Class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost extends AbstractAnytimeSupervisedBatchLearner<InputType,CategoryType,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>> implements Serializable

Serialized Fields

weakLearner

BatchLearner<DataType,ResultType> weakLearner
The "weak learner" that must learn from the weighted input-output pairs on each iteration.

Class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner extends AbstractSupervisedBatchAndIncrementalLearner<InputType,CategoryType,VotingCategorizerEnsemble<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>>> implements Serializable

Serialized Fields

learner

IncrementalLearner<DataType,ResultType> learner
The base learner used for each ensemble member.


ensembleSize

int ensembleSize
The size of the ensemble to create. Must be positive.


percentToSample

double percentToSample
The percentage of the data to sample for each ensemble member. Must be positive. Used as a parameter to the Poisson distribution to determine the number of samples for each ensemble member.


random

Random random
The random number generator to use.

Class gov.sandia.cognition.learning.algorithm.ensemble.VotingCategorizerEnsemble extends AbstractDiscriminantCategorizer<InputType,CategoryType,Double> implements Serializable

Serialized Fields

members

List<E> members
The members of the ensemble.

Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble extends AbstractWeightedEnsemble<MemberType extends Evaluator<? super InputType,? extends Number>> implements Serializable

Serialized Fields

bias

double bias
The initial offset value that the ensemble outputs are added to.

Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAveragingEnsemble extends AbstractWeightedEnsemble<MemberType extends Evaluator<? super InputType,? extends Number>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble extends AbstractDiscriminantBinaryCategorizer<InputType> implements Serializable

Serialized Fields

members

List<E> members
The members of the ensemble.

Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble extends AbstractCategorizer<InputType,CategoryType> implements Serializable

Serialized Fields

members

List<E> members
The members of the ensemble.


Package gov.sandia.cognition.learning.algorithm.genetic

Class gov.sandia.cognition.learning.algorithm.genetic.EvaluatedGenome extends Object implements Serializable

Serialized Fields

genome

Object genome
The genome that was evaluated.


cost

double cost
The cost associated with a Genome.

Class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm extends AbstractAnytimeBatchLearner<CostParametersType,GenomeType> implements Serializable

Serialized Fields

costFunction

CostFunction<EvaluatedType,CostParametersType> costFunction
The cost function for genomes.


reproducer

Reproducer<GenomeType> reproducer
The reproduction function for genomes.


bestSoFar

EvaluatedGenome<GenomeType> bestSoFar
The best genome found so far.


maxIterationsWithoutImprovement

int maxIterationsWithoutImprovement
The maximum number of iterations to go without improvement before stopping


iterationsWithoutImprovement

int iterationsWithoutImprovement
The number of iterations since the last improvement.


population

Collection<E> population
The population of genomes.


initialPopulation

Collection<E> initialPopulation
The initial population of genomes

Class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm extends GeneticAlgorithm<CostParametersType,GenomeType> implements Serializable

Serialized Fields

evaluateTasks

ArrayList<E> evaluateTasks
Parallel tasks that evaluate genome fitness


Package gov.sandia.cognition.learning.algorithm.genetic.reproducer

Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.CrossoverReproducer extends Object implements Serializable

Serialized Fields

selector

Selector<GenomeType> selector
The selector to use to select the population.


crossoverFunction

CrossoverFunction<GenomeType> crossoverFunction
The crossover function to use.

Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MultiReproducer extends Object implements Serializable

Serialized Fields

reproducers

Collection<E> reproducers
The reproducers to use for reproducing.

Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MutationReproducer extends Object implements Serializable

Serialized Fields

perturber

Perturber<PerturbedType> perturber
The perturber to use for mutation.


selector

Selector<GenomeType> selector
The selector to use to select the population.

Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.VectorizableCrossoverFunction extends AbstractRandomized implements Serializable

Serialized Fields

probabilityCrossover

double probabilityCrossover
Probability that an element in the child will come from vector2, and with probability (1-probabilityCrossover) the element will come from vector1. Thus, probabilityCrossover==0.0 means that all elements will come from vector1 and probabilityCrossover==1.0 means that all elements will come from vector2, probabilityCrossover==0.5 has maximum entropy in terms of where the elements of the child vector came from


Package gov.sandia.cognition.learning.algorithm.genetic.selector

Class gov.sandia.cognition.learning.algorithm.genetic.selector.AbstractSelector extends Object implements Serializable

Class gov.sandia.cognition.learning.algorithm.genetic.selector.TournamentSelector extends AbstractSelector<GenomeType> implements Serializable

Serialized Fields

percent

double percent
The percent of the population to select.


tournamentSize

int tournamentSize
The size of the tournament.


random

Random random
The random number generator to use.


Package gov.sandia.cognition.learning.algorithm.gradient

Class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

deltaSize

double deltaSize
Size of the finite-difference unit vectors, typically ~1e-5


function

VectorizableVectorFunction function
Internal VectorizableVectorFunction to consider


Package gov.sandia.cognition.learning.algorithm.hmm

Class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm extends AbstractAnytimeBatchLearner<DataType,HiddenMarkovModel<ObservationType>> implements Serializable

Serialized Fields

distributionLearner

BatchLearner<DataType,ResultType> distributionLearner
Learner for the Distribution Functions of the HMM.


result

HiddenMarkovModel<ObservationType> result
Result of the Baum-Welch Algorithm


initialGuess

HiddenMarkovModel<ObservationType> initialGuess
Initial guess for the iterations.


lastLogLikelihood

double lastLogLikelihood
Last Log Likelihood of the iterations


reestimateInitialProbabilities

boolean reestimateInitialProbabilities
Flag to re-estimate the initial probability Vector.

Class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm extends AbstractBaumWelchAlgorithm<ObservationType,Collection<? extends ObservationType>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel extends MarkovChain implements Serializable

Serialized Fields

emissionFunctions

Collection<E> emissionFunctions
The PDFs that emit symbols from each state.

Class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain extends AbstractCloneableSerializable implements Serializable

Serialized Fields

initialProbability

Vector initialProbability
Initial probability Vector over the states. Each entry must be nonnegative and the Vector must sum to 1.


transitionProbability

Matrix transitionProbability
Transition probability matrix. The entry (i,j) is the probability of transition from state "j" to state "i". As a corollary, all entries in the Matrix must be nonnegative and the columns of the Matrix must sum to 1.

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm extends BaumWelchAlgorithm<ObservationType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

weightedValues

ArrayList<E> weightedValues
Weighted values for the PDF estimator.


distributionLearner

BatchLearner<DataType,ResultType> distributionLearner
My copy of the PDF estimator.


gammas

ArrayList<E> gammas
Gammas used to weight the learner samples.


index

int index
Index into the gammas to pull the weights.

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel extends HiddenMarkovModel<ObservationType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ComputeTransitionsTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

alphan

Vector alphan
Alpha at time n.


betanp1

Vector betanp1
Alpha at time n.


bnp1

Vector bnp1
b at time n+1.

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.LogLikelihoodTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

data

Collection<E> data
Data to compute the log-likelihood of

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.NormalizeTransitionTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

A

Matrix A
Matrix to normalize.


j

int j
Column to normalize.

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ObservationLikelihoodTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

observations

Collection<E> observations
Observations


distributionFunction

ProbabilityFunction<DataType> distributionFunction
The PDF.

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.StateObservationLikelihoodTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

alpha

Vector alpha
Alpha at time n.


beta

Vector beta
Beta at time n.

Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ViterbiTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

destinationState

int destinationState
Destination state for the Viterbi Recursion.


delta

Vector delta
Previous value of the Viterbi Recursion.


Package gov.sandia.cognition.learning.algorithm.minimization

Class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer extends AbstractAnytimeBatchLearner<EvaluatorType extends Evaluator<? super InputType,? extends OutputType>,InputOutputPair<InputType,OutputType>> implements Serializable

Serialized Fields

tolerance

double tolerance
Tolerance of the minimization algorithm, must be >= 0.0


result

InputOutputPair<InputType,OutputType> result
Resulting minimum input-output pair


initialGuess

Object initialGuess
Initial guess of the minimization routine

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerBFGS extends FunctionMinimizerQuasiNewton implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient extends AbstractAnytimeFunctionMinimizer<Vector,Double,DifferentiableEvaluator<? super Vector,Double,Vector>> implements Serializable

Serialized Fields

lineMinimizer

LineMinimizer<EvaluatorType extends Evaluator<Double,Double>> lineMinimizer
Work-horse algorithm that minimizes the function along a direction


lineFunction

DirectionalVectorToDifferentiableScalarFunction lineFunction
Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor


gradient

Vector gradient
Gradient at the current guess

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDFP extends FunctionMinimizerQuasiNewton implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell extends AbstractAnytimeFunctionMinimizer<Vector,Double,Evaluator<? super Vector,Double>> implements Serializable

Serialized Fields

lineMinimizer

LineMinimizer<EvaluatorType extends Evaluator<Double,Double>> lineMinimizer
Work-horse algorithm that minimizes the function along a direction


directionSet

List<E> directionSet
Matrix where the columns indicate the directions of minimization


lineFunction

DirectionalVectorToScalarFunction lineFunction
Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerFletcherReeves extends FunctionMinimizerConjugateGradient implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent extends AbstractAnytimeFunctionMinimizer<Vector,Double,DifferentiableEvaluator<? super Vector,Double,Vector>> implements Serializable

Serialized Fields

learningRate

double learningRate
The learning rate (or step size), must be (0,1], typically ~0.1


momentum

double momentum
The momentum rate, must be [0,1), typically ~0.8


previousDelta

Vector previousDelta
Previous input change, used for adding momentum

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerLiuStorey extends FunctionMinimizerConjugateGradient implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead extends AbstractAnytimeFunctionMinimizer<Vector,Double,Evaluator<? super Vector,Double>> implements Serializable

Serialized Fields

simplex

ArrayList<E> simplex
InputOutputPairs that define the simplex


simplexInputSum

Vector simplexInputSum
A running sum of the inputs of the simplex, used for reflection


lineFunction

DirectionalVectorToScalarFunction lineFunction
Function that defines the simplex growth direction

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerPolakRibiere extends FunctionMinimizerConjugateGradient implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton extends AbstractAnytimeFunctionMinimizer<Vector,Double,DifferentiableEvaluator<? super Vector,Double,Vector>> implements Serializable

Serialized Fields

lineMinimizer

LineMinimizer<EvaluatorType extends Evaluator<Double,Double>> lineMinimizer
Work-horse algorithm that minimizes the function along a direction


lineFunction

DirectionalVectorToDifferentiableScalarFunction lineFunction
Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor


hessianInverse

Matrix hessianInverse
Estimated inverse of the Hessian (second derivative)


gradient

Vector gradient
Gradient at the current guess


dimensionality

int dimensionality
The dimensionality of the input space


Package gov.sandia.cognition.learning.algorithm.minimization.line

Class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer extends AbstractAnytimeFunctionMinimizer<Double,Double,EvaluatorType extends Evaluator<Double,Double>> implements Serializable

Serialized Fields

bracket

LineBracket bracket
LineBracket bounding a local minimum.


validBracket

boolean validBracket
Flag indicating if the algorithm has already found a valid bracket on a local minimum.


interpolator

LineBracketInterpolator<EvaluatorType extends Evaluator<Double,Double>> interpolator
Type of algorithm to fit data points and find an interpolated minimum to the known points.


initialGuessFunctionValue

Double initialGuessFunctionValue
Function value at the initialGuess, may be null.


initialGuessSlope

Double initialGuessSlope
Function slope at the initialGuess, may be null.

Class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToDifferentiableScalarFunction extends DirectionalVectorToScalarFunction implements Serializable

Serialized Fields

lastGradient

InputOutputPair<InputType,OutputType> lastGradient
Last gradient information

Class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Serialized Fields

vectorOffset

Vector vectorOffset
Vector offset to scale in the specified direction


direction

Vector direction
Directional vector for optimization


vectorScalarFunction

Evaluator<InputType,OutputType> vectorScalarFunction
Function that maps a Vector onto a Double


lastEvaluation

DefaultInputOutputPair<InputType,OutputType> lastEvaluation
Cache for the last input/output that was evaluated, so that we can avoid using it again in the differentiate method.

Class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet extends DefaultInputOutputPair<Double,Double> implements Serializable

Serialized Fields

slope

Double slope
Slope (first derivative) at the given point

Class gov.sandia.cognition.learning.algorithm.minimization.line.LineBracket extends AbstractCloneableSerializable implements Serializable

Serialized Fields

lowerBound

InputOutputSlopeTriplet lowerBound
Lower bound of the bracket.


upperBound

InputOutputSlopeTriplet upperBound
Upper bound of the bracket.


otherPoint

InputOutputSlopeTriplet otherPoint
Another (optional) point associated with the bracket.

Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking extends AbstractAnytimeLineMinimizer<Evaluator<Double,Double>> implements Serializable

Serialized Fields

sufficientDecrease

double sufficientDecrease
Sufficient decrease condition, must be (0,1). Smaller values (0.1) result in more accurate searches, larger values (0.9) tend to be easier to satisfy.


geometricDecrease

double geometricDecrease
Amount to decrease the step amount each iteration.


numericalDerivative

boolean numericalDerivative
Flag whether or not to use the numerical differentiation.


stepValue

double stepValue
Current value of the step size.

Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased extends AbstractAnytimeLineMinimizer<DifferentiableUnivariateScalarFunction> implements Serializable

Serialized Fields

minFunctionValue

double minFunctionValue
Minimum value of the target function. In other words, the user will accept a solution less than or equal to minFunctionValue. For many applications 0.0 is a likely candidate (for cost functions, metrics, least squares, etc.)


direction

double direction
Direction of the search. Because Fletcher assumes the slope of the initialGuess is less than 0.0, we have to flip around the direction of search if the initial guess has positive slope. Thus, direction=1.0 means that the initial slope was negative, while direction=-1.0 means that the initial slope was positive.


internalFunction

LineMinimizerDerivativeBased.InternalFunction internalFunction
Internal function used to map/remap/unmap the search direction.


wolfe

WolfeConditions wolfe
The Wolfe conditions define approximate line search stopping criteria.


maxX

double maxX
Maximum value of x in the search space. That is, the minimizer will not be greater than maxX.

Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeFree extends AbstractAnytimeLineMinimizer<Evaluator<Double,Double>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions extends AbstractCloneableSerializable implements Serializable

Serialized Fields

originalPoint

InputOutputSlopeTriplet originalPoint
Original point to store, slope must be less than 0.0.


slopeCondition

double slopeCondition
Slope condition parameter for the Goldstein condition, must be less than curvatureCondition and on the interval (0,1).


curvatureCondition

double curvatureCondition
Curvature condition for the curvature condition, must be greater than slopeCondition and on the interval (0,1).


Package gov.sandia.cognition.learning.algorithm.minimization.line.interpolator

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

tolerance

double tolerance
Tolerance of the interpolator to collinear or identical points

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolatorPolynomial extends AbstractLineBracketInterpolator<EvaluatorType extends Evaluator<Double,Double>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorBrent extends AbstractLineBracketInterpolator<Evaluator<Double,Double>> implements Serializable

Serialized Fields

parabolicInterpolator

LineBracketInterpolatorParabola parabolicInterpolator
Non-slope based parabolic interpolator.


goldenInterpolator

LineBracketInterpolatorGoldenSection goldenInterpolator
Golden-section step interpolator.

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorGoldenSection extends AbstractLineBracketInterpolator<Evaluator<Double,Double>> implements Serializable

Serialized Fields

linearInterpolator

LineBracketInterpolatorLinear linearInterpolator
Back-up interpolator using the secant method.

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorHermiteCubic extends AbstractLineBracketInterpolatorPolynomial<DifferentiableUnivariateScalarFunction> implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorHermiteParabola extends AbstractLineBracketInterpolatorPolynomial<DifferentiableUnivariateScalarFunction> implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorLinear extends AbstractLineBracketInterpolatorPolynomial<Evaluator<Double,Double>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorParabola extends AbstractLineBracketInterpolatorPolynomial<Evaluator<Double,Double>> implements Serializable


Package gov.sandia.cognition.learning.algorithm.nearest

Class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor extends AbstractNearestNeighbor<InputType,OutputType> implements Serializable

Serialized Fields

k

int k
Number of neighbors to consider, must be greater than zero


averager

Summarizer<DataType,SummaryType> averager
Creates a single object from a collection of data

Class gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor extends DefaultDivergenceFunctionContainer<InputType,InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive extends AbstractKNearestNeighbor<InputType,OutputType> implements Serializable

Serialized Fields

data

Collection<E> data
Underlying data for the classifier

Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive.Learner extends KNearestNeighborExhaustive<InputType,OutputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive.Neighbor extends AbstractCloneableSerializable implements Serializable

Serialized Fields

value

Object value
Output value.


divergence

double divergence
Divergence associated with this value.

Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree extends AbstractKNearestNeighbor<InputType extends Vectorizable,OutputType> implements Serializable

Serialized Fields

data

KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> data
KDTree that holds the data to search for neighbors.

Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree.Learner extends KNearestNeighborKDTree<InputType extends Vectorizable,OutputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive extends AbstractNearestNeighbor<InputType,OutputType> implements Serializable

Serialized Fields

data

LinkedList<E> data
The data that nearest-neighbor is performed over.

Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive.Learner extends DefaultDivergenceFunctionContainer<InputType,InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree extends AbstractNearestNeighbor<InputType extends Vectorizable,OutputType> implements Serializable

Serialized Fields

data

KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> data
KDTree that holds the data to search for neighbors.

Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree.Learner extends NearestNeighborKDTree<InputType extends Vectorizable,OutputType> implements Serializable


Package gov.sandia.cognition.learning.algorithm.pca

Class gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis extends AbstractCloneableSerializable implements Serializable

Serialized Fields

numComponents

int numComponents
Number of components to extract from the data, must be greater than zero


result

PrincipalComponentsAnalysisFunction result
Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.

Class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm extends AbstractAnytimeBatchLearner<Collection<Vector>,PrincipalComponentsAnalysisFunction> implements Serializable

Serialized Fields

learningRate

double learningRate
Learning rate, or step size, (0,1], typically ~0.1


numComponents

int numComponents
Number of components to extract from the data, must be greater than zero


result

PrincipalComponentsAnalysisFunction result
Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.


components

ArrayList<E> components
Components that have been extracted from the input data, each component has the same dimensions as the input data and the size of the ArrayList is numComponents


mean

Vector mean
Sample mean of the training data. This is subtracted from the training data before GHA is executed.


minChange

double minChange
Minimum change below which to stop iterating, greater than or equal to zero, typically 1e-10

Class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis extends DefaultKernelContainer<DataType> implements Serializable

Serialized Fields

componentCount

int componentCount
The number of components to create from the analysis. Must be positive.


centerData

boolean centerData
Whether or not the data should be centered before doing KPCA.

Class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function extends DefaultKernelContainer<DataType> implements Serializable

Serialized Fields

data

List<E> data
The data that the KPCA was performed over. Each one corresponds to a column in the components matrix.


components

Matrix components
The matrix of components for the function. The number of rows is the dimensionality of the reduction. The number of columns is equal to the number of data points that the KPCA was done over.


centerData

boolean centerData
A flag indicating if the incoming data needs to be centered or not. Unless the data is being pre-centered, this should be true.


kernelMatrix

Matrix kernelMatrix
The kernel matrix for all the data the KPCA was done over. It is a square matrix whose size is equal to the data.

Class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction extends AbstractCloneableSerializable implements Serializable

Serialized Fields

mean

Vector mean
Sample mean of the data, which is subtracted from input data to yield zero-mean inputs


dimensionReducer

MultivariateDiscriminant dimensionReducer
Function that maps a high-dimension input space onto a (hopefully) simple low-dimensional output space capturing the directions of maximum variance (information gain)

Class gov.sandia.cognition.learning.algorithm.pca.ThinSingularValueDecomposition extends AbstractPrincipalComponentsAnalysis implements Serializable


Package gov.sandia.cognition.learning.algorithm.perceptron

Class gov.sandia.cognition.learning.algorithm.perceptron.AbstractKernelizableBinaryCategorizerOnlineLearner extends AbstractOnlineLinearBinaryCategorizerLearner implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable

Serialized Fields

updateBias

boolean updateBias
An option controlling whether or not the bias is updated or not. Individual algorithm implementations choose the default value for this.

Class gov.sandia.cognition.learning.algorithm.perceptron.AbstractOnlineLinearBinaryCategorizerLearner extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,Boolean,LinearBinaryCategorizer> implements Serializable

Serialized Fields

vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The factory to create weight vectors.

Class gov.sandia.cognition.learning.algorithm.perceptron.AggressiveRelaxedOnlineMaximumMarginAlgorithm extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.Ballseptron extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable

Serialized Fields

radius

double radius
The radius enforced by the algorithm.

Class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,CategoryType,LinearMultiCategorizer<CategoryType>> implements Serializable

Serialized Fields

minMargin

double minMargin
The minimum margin to enforce. Must be non-negative.


vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The factory to create weight vectors.

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm extends AbstractLinearCombinationOnlineLearner implements Serializable

Serialized Fields

minMargin

double minMargin
The minimum margin to enforce. Must be non-negative.

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>> implements Serializable

Serialized Fields

minMargin

double minMargin
The minimum margin to enforce. Must be non-negative.


vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The factory to create weight vectors.

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate extends OnlineMultiPerceptron<CategoryType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.UniformUpdate extends OnlineMultiPerceptron<CategoryType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron extends AbstractLinearCombinationOnlineLearner implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin extends OnlinePassiveAggressivePerceptron implements Serializable

Serialized Fields

aggressiveness

double aggressiveness
The aggressiveness parameter (C), which is the trade-off between aggressive updating to meet an incorrect example and keeping history around.

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.LinearSoftMargin extends OnlinePassiveAggressivePerceptron.AbstractSoftMargin implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.QuadraticSoftMargin extends OnlinePassiveAggressivePerceptron.AbstractSoftMargin implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron extends AbstractLinearCombinationOnlineLearner implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron extends OnlinePassiveAggressivePerceptron.QuadraticSoftMargin implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron extends AbstractLinearCombinationOnlineLearner implements Serializable

Serialized Fields

lambda

double lambda
The lambda parameter for controlling how much shifting occurs.

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron.LinearResult extends LinearBinaryCategorizer implements Serializable

Serialized Fields

errorCount

long errorCount
The number of errors made by the categorizer so far.

Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineVotedPerceptron extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,Boolean,WeightedBinaryEnsemble<Vectorizable,LinearBinaryCategorizer>> implements Serializable

Serialized Fields

vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The factory to create weight vectors.

Class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,Boolean,LinearBinaryCategorizer> implements Serializable

Serialized Fields

marginPositive

double marginPositive
The positive margin to enforce.


marginNegative

double marginNegative
The negative margin to enforce.


vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The VectorFactory to use to create vectors.


result

LinearBinaryCategorizer result
The result categorizer.


errorCount

int errorCount
The number of errors on the most recent iteration.

Class gov.sandia.cognition.learning.algorithm.perceptron.RelaxedOnlineMaximumMarginAlgorithm extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.Winnow extends AbstractOnlineLinearBinaryCategorizerLearner implements Serializable

Serialized Fields

weightUpdate

double weightUpdate
The amount of the weight update (alpha). Must be greater than 1.


demoteToZero

boolean demoteToZero
An option to demote to zero.


weightUpdateInverse

double weightUpdateInverse
The cached value of the inverse of weight update (commonly alpha or 1 + epsilon).


Package gov.sandia.cognition.learning.algorithm.perceptron.kernel

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineBudgetedKernelBinaryCategorizerLearner extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable

Serialized Fields

budget

int budget
The budget of the number of examples to keep. Must be positive.

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner extends AbstractSupervisedBatchAndIncrementalLearner<InputType,Boolean,DefaultKernelBinaryCategorizer<InputType>> implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The kernel to use.

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Basic extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Greedy extends Forgetron<InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Result extends DefaultKernelBinaryCategorizer<InputType> implements Serializable

Serialized Fields

errorCount

long errorCount
The number of errors that the categorizer has made in the learning step.


q

double q
The value of Q for the algorithm.

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron extends AbstractAnytimeSupervisedBatchLearner<InputType,Boolean,KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>> implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The kernel to use.


result

KernelBinaryCategorizer<InputType,EntryType extends WeightedValue<? extends InputType>> result
The result categorizer.


errorCount

int errorCount
The number of errors on the most recent iteration.


supportsMap

LinkedHashMap<K,V> supportsMap
The mapping of weight objects to non-zero weighted examples (support vectors).

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelBinaryCategorizerOnlineLearnerAdapter extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable

Serialized Fields

learner

KernelizableBinaryCategorizerOnlineLearner learner
The wrapped kernelizable learner.

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron extends AbstractAnytimeSupervisedBatchLearner<InputType,Boolean,DefaultKernelBinaryCategorizer<InputType>> implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The kernel to use.


marginPositive

double marginPositive
The positive margin to enforce.


marginNegative

double marginNegative
The negative margin to enforce.


result

DefaultKernelBinaryCategorizer<InputType> result
The result categorizer.


errorCount

int errorCount
The number of errors on the most recent iteration.


supportsMap

LinkedHashMap<K,V> supportsMap
The mapping of weight objects to non-zero weighted examples (support vectors).

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelPerceptron extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelRandomizedBudgetPerceptron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable

Serialized Fields

random

Random random
The random number generator.

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable

Serialized Fields

eta

double eta
The eta parameter, which ends up controlling the number of supports created. Must be non-negative.

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron.LinearSoftMargin extends Projectron<InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.RemoveOldestKernelPerceptron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Stoptron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable


Package gov.sandia.cognition.learning.algorithm.regression

Class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer extends AnytimeAlgorithmWrapper<ResultType extends VectorizableVectorFunction,FunctionMinimizer<Vector,Double,? super EvaluatorType extends Evaluator<? super Vector,? extends Double>>> implements Serializable

Serialized Fields

objectToOptimize

VectorizableVectorFunction objectToOptimize
Object that is being optimized.


result

VectorizableVectorFunction result
Resulting value


costFunction

SupervisedCostFunction<InputType,TargetType> costFunction
Cost function to compute the cost of objectToOptimize

Class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer extends AbstractAnytimeSupervisedBatchLearner<Vector,Vector,ResultType extends VectorizableVectorFunction> implements Serializable

Serialized Fields

objectToOptimize

VectorizableVectorFunction objectToOptimize
GradientDescendable whose parameters result minimize the cost function


result

VectorizableVectorFunction result
Result to return


tolerance

double tolerance
Stopping criterion for the algorithm, typically ~1e-5


costFunction

SupervisedCostFunction<InputType,TargetType> costFunction
Cost function that computes the cost of the object to optimize


resultCost

Double resultCost
Cost of the result

Class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation extends LeastSquaresEstimator implements Serializable

Serialized Fields

lineMinimizer

LineMinimizer<EvaluatorType extends Evaluator<Double,Double>> lineMinimizer
Workhorse algorithm that finds the minimum along a particular direction


reductionTest

double reductionTest
Reduction test for switching between BFGS and Levenberg-Marquardt, must be [0,1]. Lower values result in more Levenberg-Marquardt steps, larger values result in more BFGS steps.


dampingFactorDivisor

double dampingFactorDivisor
Amount to modify the damping factor, typically 2.0 or 10.0


lastCost

SumSquaredErrorCostFunction.Cache lastCost
Last value of the parameter cost


lineFunction

DirectionalVectorToDifferentiableScalarFunction lineFunction
Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor


hessianInverse

Matrix hessianInverse
Estimated inverse of the Hessian (second derivative)


dampingFactor

double dampingFactor
Damping factor for the Levenberg-Marquardt ridge regression

Class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm extends LeastSquaresEstimator implements Serializable

Serialized Fields

lineMinimizer

LineMinimizer<EvaluatorType extends Evaluator<Double,Double>> lineMinimizer
Workhorse algorithm that finds the minimum along a particular direction


lineFunction

DirectionalVectorToDifferentiableScalarFunction lineFunction
Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor

Class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression extends AbstractAnytimeSupervisedBatchLearner<InputType,Double,KernelScalarFunction<InputType>> implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The kernel to use.


minSensitivity

double minSensitivity
The bound on sensitivity.


result

KernelScalarFunction<InputType> result
The result categorizer.


errorCount

int errorCount
The number of errors on the most recent iteration.

Class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression extends AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,Evaluator<? super InputType,? extends OutputType>> implements Serializable

Serialized Fields

result

Evaluator<InputType,OutputType> result
DecoupledVectorFunction that is being optimized


iterationLearner

SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> iterationLearner
Internal learning algorithm that computes optimal solutions given the current weightedData. The iterationLearner should operate on WeightedInputOutputPairs (we have a hard time enforcing this, as many learning algorithms operate both on InputOutputPairs and WeightedInputOutputPairs)


kernelWeightingFunction

Kernel<InputType> kernelWeightingFunction
Kernel function that provides the weighting for the estimate error, generally the Kernel should weight accurate estimates higher than inaccurate estimates.


tolerance

double tolerance
Tolerance before stopping the algorithm


weightedData

ArrayList<E> weightedData
Weighted copy of the data

Class gov.sandia.cognition.learning.algorithm.regression.LeastSquaresEstimator extends AbstractParameterCostMinimizer<GradientDescendable,SumSquaredErrorCostFunction> implements Serializable

Class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation extends LeastSquaresEstimator implements Serializable

Serialized Fields

iterationsWithoutImprovement

int iterationsWithoutImprovement
Number of sequential unsuccessful iterations without a cost-reducing step


maxIterationsWithoutImprovement

int maxIterationsWithoutImprovement
Maximum number of iterations without improvement before stopping


dampingFactor

double dampingFactor
Current damping factor for the ridge regression


dampingFactorDivisor

double dampingFactorDivisor
Divisor of the damping factor on a successful iteration, must be greater then 1.0, typically ~10.0


bestParameters

Vector bestParameters
Parameters used to generate the lastCost


bestParametersCost

SumSquaredErrorCostFunction.Cache bestParametersCost
Cost associated with lastParameters

Class gov.sandia.cognition.learning.algorithm.regression.LinearBasisRegression extends AbstractCloneableSerializable implements Serializable

Serialized Fields

inputToVectorMap

Evaluator<InputType,OutputType> inputToVectorMap
Function that maps the InputType to a Vector


usePseudoInverse

boolean usePseudoInverse
Flag to use a pseudoinverse. True to use the expensive, but more accurate, pseudoinverse routine. False uses a very fast, but numerically less stable LU solver. Default value is "true".

Class gov.sandia.cognition.learning.algorithm.regression.LinearRegression extends AbstractCloneableSerializable implements Serializable

Serialized Fields

usePseudoInverse

boolean usePseudoInverse
Flag to use a pseudoinverse. True to use the expensive, but more accurate, pseudoinverse routine. False uses a very fast, but numerically less stable LU solver. Default value is "true".


regularization

double regularization
L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.

Class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic extends AbstractConfidenceStatistic implements Serializable

Serialized Fields

chiSquare

double chiSquare
Gets the value of the chi-square variable, Total weighted sum-squared error between the targets and estimates


rootMeanSquaredError

double rootMeanSquaredError
Root mean-squared error of the targets and estimates


meanL1Error

double meanL1Error
Average L1-norm error (absolute value difference) between the targets and estimates


targetEstimateCorrelation

double targetEstimateCorrelation
Pearson Correlation between the targets and estimates, [-1,1]


unpredictedErrorFraction

double unpredictedErrorFraction
Fraction of variance unaccounted for in the predictions, [0,1]


numSamples

int numSamples
Number of samples used to create the Regression


numParameters

int numParameters
Number of parameters in the learned approximator


degreesOfFreedom

double degreesOfFreedom
Degrees of freedom in the Regression = numSamples-numParameters

Class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction.Learner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
Kernel that provides the weights between an input and each sample in the input dataset


learner

SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> learner
Learner that takes the Collection of WeightedInputOutputPairs from the Kernel reweighting and creates a local function approximation at the given input. I would strongly recommend using fast or closed-form learners for this.

Class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,Double,LogisticRegression.Function> implements Serializable

Serialized Fields

objectToOptimize

LogisticRegression.Function objectToOptimize
The object to optimize, used as a factory on successive runs of the algorithm.


result

LogisticRegression.Function result
Return value from the algorithm


tolerance

double tolerance
Tolerance change in weights before stopping


regularization

double regularization
L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.

Class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression.Function extends CompositeEvaluatorPair<Vectorizable,Double,Double> implements Serializable

Class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression extends AbstractCloneableSerializable implements Serializable

Serialized Fields

usePseudoInverse

boolean usePseudoInverse
Flag to use a pseudoinverse. True to use the expensive, but more accurate, pseudoinverse routine. False uses a very fast, but numerically less stable LU solver. Default value is "true".


regularization

double regularization
L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.

Class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer extends AbstractMinimizerBasedParameterCostMinimizer<VectorizableVectorFunction,DifferentiableEvaluator<Vector,Double,Vector>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree extends AbstractCloneableSerializable implements Serializable

Serialized Fields

internalFunction

VectorizableVectorFunction internalFunction
Object that we're tweaking the parameters of.


costFunction

SupervisedCostFunction<InputType,TargetType> costFunction
Cost function against which to evaluate the cost of the object.

Class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer extends AbstractMinimizerBasedParameterCostMinimizer<GradientDescendable,DifferentiableEvaluator<Vector,Double,Vector>> implements Serializable

Class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased extends AbstractCloneableSerializable implements Serializable

Serialized Fields

internalFunction

GradientDescendable internalFunction
Object that we're tweaking the parameters of.


costFunction

DifferentiableCostFunction costFunction
Cost function against which to evaluate the cost of the object.

Class gov.sandia.cognition.learning.algorithm.regression.UnivariateLinearRegression extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.algorithm.root

Class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder extends AbstractRootFinder implements Serializable

Serialized Fields

bracketer

RootBracketer bracketer
Root-bracketing algorithm.


rootBracket

LineBracket rootBracket
Gets the bracket on the root location. That is, a range of input values where a root is guaranteed to lay between.

Class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder extends AbstractAnytimeBatchLearner<Evaluator<Double,Double>,InputOutputPair<Double,Double>> implements Serializable

Serialized Fields

tolerance

double tolerance
Tolerance, where tolerances closer to zero are more accurate, and larger tolerances are less accurate. In any case, tolerance must be greater than or equal to zero.


initialGuess

double initialGuess
Initial guess of the root location.

Class gov.sandia.cognition.learning.algorithm.root.MinimizerBasedRootFinder extends AnytimeAlgorithmWrapper<InputOutputPair<Double,Double>,LineMinimizer<Evaluator<Double,Double>>> implements Serializable

Serialized Fields

internalFunction

gov.sandia.cognition.learning.algorithm.root.MinimizerBasedRootFinder.MinimizationFunction internalFunction
Internal function.

Class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander extends AbstractAnytimeBatchLearner<Evaluator<Double,Double>,LineBracket> implements Serializable

Serialized Fields

bracket

LineBracket bracket
Bracket on the root location.


initialGuess

double initialGuess
Initial guess of the root's location.

Class gov.sandia.cognition.learning.algorithm.root.RootFinderBisectionMethod extends AbstractBracketedRootFinder implements Serializable

Class gov.sandia.cognition.learning.algorithm.root.RootFinderFalsePositionMethod extends AbstractBracketedRootFinder implements Serializable

Class gov.sandia.cognition.learning.algorithm.root.RootFinderNewtonsMethod extends AbstractRootFinder implements Serializable

Serialized Fields

result

DefaultInputOutputPair<InputType,OutputType> result
Resulting estimated location of the root.


dfdx

DifferentiableEvaluator<InputType,OutputType,DerivativeType> dfdx
Internal Function variable from which we will pull the derivative. If the Evaluator is a DifferentiableEvaluator, then we will use that. Otherwise, we set up an approximation to the derivative.


stepMultiplier

double stepMultiplier
Multiplier of the current step.

Class gov.sandia.cognition.learning.algorithm.root.RootFinderRiddersMethod extends AbstractBracketedRootFinder implements Serializable

Class gov.sandia.cognition.learning.algorithm.root.RootFinderSecantMethod extends AbstractBracketedRootFinder implements Serializable

Serialized Fields

previousPoint

InputOutputSlopeTriplet previousPoint

Class gov.sandia.cognition.learning.algorithm.root.SolverFunction extends AbstractUnivariateScalarFunction implements Serializable

Serialized Fields

target

double target
internalFunction value to search for.


internalFunction

Evaluator<InputType,OutputType> internalFunction
The internal function to use.


Package gov.sandia.cognition.learning.algorithm.svm

Class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,Boolean,LinearBinaryCategorizer> implements Serializable

Serialized Fields

sampleSize

int sampleSize
The sample size requested by the user. The actual sample size may be less than this in the case that the sample size is larger than the amount of data given in the training set.


regularizationWeight

double regularizationWeight
The weight assigned to the regularization term in the algorithm, which is often represented as lambda.


random

Random random
The random number generator to use.

Class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization extends AbstractAnytimeSupervisedBatchLearner<InputType,Boolean,KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>> implements Serializable

Serialized Fields

maxPenalty

double maxPenalty
The maximum penalty parameter (C). Must be greater than 0.0.


errorTolerance

double errorTolerance
The error tolerance for the algorithm. Must be non-negative. Also known as "tol" or "tolerance".


effectiveZero

double effectiveZero
The effective value for zero to use in the computation to deal with numerical imprecision. Must be a non-negative number. Typically a very small value. Also sometimes known as epsilon.


kernelCacheSize

int kernelCacheSize
The size of the kernel cache, which is the number of kernel computations to keep cached. May be 0 to indicate that the kernel cache should not be used.


random

Random random
The random number generator to use.


kernel

Kernel<InputType> kernel
The kernel to use.

Class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation extends AbstractAnytimeSupervisedBatchLearner<InputType,Boolean,KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>> implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The kernel to use.


maxWeight

double maxWeight
The maximum weight for a support vector. Must be greater than zero.


overrelaxation

double overrelaxation
The overrelaxation parameter. Must be in (0, 2), exclusive.


minChange

double minChange
The minimum change to allow for the algorithm to keep going. If the Total change is below this, then the algorithm will stop. Must be greater than zero.


result

KernelBinaryCategorizer<InputType,EntryType extends WeightedValue<? extends InputType>> result
The result categorizer.


totalChange

double totalChange
The total change on the most recent pass.


entries

ArrayList<E> entries
The entry information that the algorithm keeps.


supportsMap

LinkedHashMap<K,V> supportsMap
The mapping of weight objects to non-zero weighted examples (support vectors).

Class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry extends DefaultWeightedValue<InputType> implements Serializable

Serialized Fields

example

InputOutputPair<InputType,OutputType> example
The example the data pertains to.


output

boolean output
The output represented as a raw boolean, to enforce that the label exists.


outputDouble

double outputDouble
The output converted to a double form (+1.0 or -1.0).


supportInserted

boolean supportInserted
Indicates if the support vector has been inserted into the map of support vectors or not. This allows us to keep the supports map to only contain the entries whose weights are non-zero.


selfKernel

double selfKernel
This is the value of the kernel applied to the example and itself. We use this value in the update step, so we can cache it for a performance boost.


previousStepWeight

double previousStepWeight
The weight of the entry on the previous step. This is used at the end of the step to calculate the total change of weights in the step.


Package gov.sandia.cognition.learning.algorithm.tree

Class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner extends AbstractIterativeAlgorithm implements Serializable

Serialized Fields

deciderLearner

DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>> deciderLearner
The learning algorithm for the decision function.

Class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode extends Object implements Serializable

Serialized Fields

parent

DecisionTreeNode<InputType,OutputType> parent
The parent node of this node.


childMap

Map<K,V> childMap
The mapping of decider decision values to child nodes. For a leaf node, this can be null or empty.


decider

Categorizer<InputType,CategoryType> decider
The decider used to make a decision as to which child use. For a leaf node, the decider should be null.


incomingValue

Object incomingValue
The incoming value for the node. Usually if this is null it means that the node is a root node.

Class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

dimensionsToConsider

int[] dimensionsToConsider
The array of dimensions for the learner to consider. If this is null, then all dimensions are considered.

Class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree extends DecisionTree<InputType,OutputType> implements Serializable

Serialized Fields

categories

Set<E> categories
The list of possible output categories.

Class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner extends AbstractDecisionTreeLearner<InputType,OutputType> implements Serializable

Serialized Fields

leafCountThreshold

int leafCountThreshold
The threshold for making a node a leaf, determined by how many instances fall in the threshold.


maxDepth

int maxDepth
The maximum depth for the tree. Ignored if less than 1.


priors

Map<K,V> priors
Prior probabilities for the different categories. If null, the priors default to the category frequencies of the training data.


trainCounts

Map<K,V> trainCounts
How often each category appears in training data.

Class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode extends AbstractDecisionTreeNode<InputType,OutputType,InteriorType> implements Serializable

Serialized Fields

outputCategory

Object outputCategory
The output category of the node. All nodes should have this, but it is absolutely required for a leaf node.

Class gov.sandia.cognition.learning.algorithm.tree.DecisionTree extends AbstractCloneableSerializable implements Serializable

Serialized Fields

rootNode

DecisionTreeNode<InputType,OutputType> rootNode
The root node of the decision tree.

Class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner extends AbstractRandomized implements Serializable

Serialized Fields

subLearner

DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>> subLearner
The decider learner for the subspace.


percentToSample

double percentToSample
The percentage of the dimensionality to sample.


vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The vector factory to use.

Class gov.sandia.cognition.learning.algorithm.tree.RegressionTree extends DecisionTree<InputType,Double> implements Serializable

Class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner extends AbstractDecisionTreeLearner<InputType,Double> implements Serializable

Serialized Fields

regressionLearner

BatchLearner<DataType,ResultType> regressionLearner
The learning algorithm for the regression function.


leafCountThreshold

int leafCountThreshold
The threshold for making a node a leaf, determined by how many instances fall in the threshold.


maxDepth

int maxDepth
The maximum depth for the tree. Ignored if less than 1.

Class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode extends AbstractDecisionTreeNode<InputType,Double,InteriorType> implements Serializable

Serialized Fields

scalarFunction

Evaluator<InputType,OutputType> scalarFunction
The function to apply for leaf nodes.


value

double value
The value stored at the tree node. It is used as a backup value if no scalar function exists for the node but the output is requested.

Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdGiniImpurityLearner extends AbstractVectorThresholdMaximumGainLearner<OutputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdHellingerDistanceLearner extends AbstractVectorThresholdMaximumGainLearner<OutputType> implements Serializable

Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner extends AbstractVectorThresholdMaximumGainLearner<OutputType> implements Serializable

Serialized Fields

categories

ArrayList<E> categories

categoryPriors

double[] categoryPriors

categoryCounts

int[] categoryCounts

categoryProbabilities

double[] categoryProbabilities
Following is scratch space used when computing weighted entropy. It is declared here so it can be allocated once, instead of during every entropy evaluation.

Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.data

Class gov.sandia.cognition.learning.data.AbstractInputOutputPair extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.data.AbstractTargetEstimatePair extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.data.AbstractValueDiscriminantPair extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.data.DefaultInputOutputPair extends AbstractInputOutputPair<InputType,OutputType> implements Serializable

Serialized Fields

input

Object input
The input.


output

Object output
The output associated with the input.

Class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair extends AbstractTargetEstimatePair<TargetType,EstimateType> implements Serializable

Serialized Fields

target

Object target
Target (ground-truth) value.


estimate

Object estimate
Estimate (prediction) of the target value.

Class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair extends AbstractValueDiscriminantPair<ValueType,DiscriminantType extends Comparable<? super DiscriminantType>> implements Serializable

Serialized Fields

value

Object value
The value.


discriminant

Comparable<T> discriminant
The discriminant.

Class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair extends DefaultInputOutputPair<InputType,OutputType> implements Serializable

Serialized Fields

weight

double weight
Weighting term for the InputOutputPair.

Class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair extends DefaultTargetEstimatePair<TargetType,EstimateType> implements Serializable

Serialized Fields

weight

double weight
The weight.

Class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant extends DefaultWeightedValue<ValueType> implements Serializable

Class gov.sandia.cognition.learning.data.RandomDataPartitioner extends AbstractRandomized implements Serializable

Serialized Fields

trainingPercent

double trainingPercent
The percentage of training data.


Package gov.sandia.cognition.learning.data.feature

Class gov.sandia.cognition.learning.data.feature.DelayFunction extends AbstractStatefulEvaluator<DataType,DataType,FiniteCapacityBuffer<DataType>> implements Serializable

Serialized Fields

delaySamples

int delaySamples
Number of samples to delay the value

Class gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor extends AbstractStatefulEvaluator<Vector,Vector,FiniteCapacityBuffer<Vector>> implements Serializable

Serialized Fields

maxBufferSize

int maxBufferSize
maximum number of vectors to hold in the buffer

Class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

gaussian

MultivariateGaussian gaussian
The underlying Gaussian.


covarianceInverseSquareRoot

Matrix covarianceInverseSquareRoot
The square root of the inverse of the covariance.

Class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

defaultCovariance

double defaultCovariance
The default covariance. Added to the diagonal to prevent it from becoming singular.

Class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.FullCovarianceLearner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

defaultCovariance

double defaultCovariance
The default covariance. Added to the diagonal to prevent it from becoming singular.

Class gov.sandia.cognition.learning.data.feature.RandomSubspace extends AbstractRandomized implements Serializable

Serialized Fields

size

int size
The size of the random subspace to create, which is the number of dimensions that are chosen.


vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The vector factory for the sub vector evaluator to use.

Class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer extends AbstractUnivariateScalarFunction implements Serializable

Serialized Fields

mean

double mean
The mean of normalization.


variance

double variance
The variance for normalization.


standardDeviation

double standardDeviation
The cached value of the standard deviation for normalization.

Class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer.Learner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

outlierPercent

double outlierPercent
The percentage of outliers to exclude from learning.


Package gov.sandia.cognition.learning.experiment

Class gov.sandia.cognition.learning.experiment.AbstractLearningExperiment extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.experiment.AbstractValidationFoldExperiment extends AbstractLearningExperiment implements Serializable

Serialized Fields

foldCreator

ValidationFoldCreator<InputDataType,FoldDataType> foldCreator
The method to use to create the validation folds.


numTrials

int numTrials
The number of trials in the experiment, which is the number of folds in the experiment.

Class gov.sandia.cognition.learning.experiment.CrossFoldCreator extends AbstractRandomized implements Serializable

Serialized Fields

numFolds

int numFolds
The number of folds to create.

Class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment extends AbstractValidationFoldExperiment<InputDataType,FoldDataType> implements Serializable

Serialized Fields

performanceEvaluator

PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
The evaluator to use to compute the performance of the learned object on each fold.


summarizer

Summarizer<DataType,SummaryType> summarizer
The summarizer for summarizing the result of the performance evaluator from all the folds.


statisticalTest

NullHypothesisEvaluator<DataType> statisticalTest
The statistical test to use to determine if the two learners are significantly different.


learners

Pair<FirstType,SecondType> learners
The learners that the experiment is being performed on.


statistics

DefaultPair<FirstType,SecondType> statistics
The performance evaluations made during the experiment.


confidence

ConfidenceStatistic confidence
The confidence statistic generated from the underlying performance statistics.


summaries

DefaultPair<FirstType,SecondType> summaries
The summaries of performance.

Class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment extends AbstractLearningExperiment implements Serializable

Serialized Fields

numTrials

int numTrials
The number of trials to repeat the learning.


performanceEvaluator

PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
The evaluator to use to compute the performance of the learned object on each fold.


summarizer

Summarizer<DataType,SummaryType> summarizer
The summarizer for summarizing the result of the performance evaluator from all the folds.


learner

BatchLearner<DataType,ResultType> learner
The learner that the experiment is run on.


statistics

ArrayList<E> statistics
The performance evaluations made during the experiment.


summary

Object summary
The summary of the performance evaluations made at the end of the experiment.

Class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment extends AbstractValidationFoldExperiment<InputDataType,FoldDataType> implements Serializable

Serialized Fields

performanceEvaluator

PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
The evaluator to use to compute the performance of the learned object on each fold.


summarizer

Summarizer<DataType,SummaryType> summarizer
The summarizer for summarizing the result of the performance evaluator from all the folds.


learner

BatchLearner<DataType,ResultType> learner
The learner that the experiment is run on.


statistics

ArrayList<E> statistics
The performance evaluations made during the experiment.


summary

Object summary
The summary of the performance evaluations made at the end of the experiment.

Class gov.sandia.cognition.learning.experiment.LeaveOneOutFoldCreator extends Object implements Serializable

Class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment extends AbstractLearningExperiment implements Serializable

Serialized Fields

performanceEvaluator

PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
The evaluator to use to compute the performance of the learned object on each fold.


summarizer

Summarizer<DataType,SummaryType> summarizer
The summarizer for summarizing the result of the performance evaluator from all the folds.


numTrials

int numTrials
The number of trials in the experiment, which is the number of folds in the experiment.


statistics

ArrayList<E> statistics
The performance evaluations made during the experiment.


summary

Object summary
The summary of the performance evaluations made at the end of the experiment.

Class gov.sandia.cognition.learning.experiment.ParallelLearnerValidationExperiment extends LearnerValidationExperiment<InputDataType,FoldDataType,LearnedType,StatisticType,SummaryType> implements Serializable

Class gov.sandia.cognition.learning.experiment.RandomByTwoFoldCreator extends AbstractRandomized implements Serializable

Serialized Fields

numSplits

int numSplits
The number of splits. The number of folds is twice this number.

Class gov.sandia.cognition.learning.experiment.RandomFoldCreator extends Object implements Serializable

Serialized Fields

numFolds

int numFolds
The number of folds to create.


partitioner

RandomizedDataPartitioner<DataType> partitioner
The partitioner used for each fold.

Class gov.sandia.cognition.learning.experiment.SupervisedLearnerComparisonExperiment extends LearnerComparisonExperiment<InputOutputPair<InputType,OutputType>,InputOutputPair<InputType,OutputType>,Evaluator<? super InputType,OutputType>,StatisticType,SummaryType> implements Serializable

Class gov.sandia.cognition.learning.experiment.SupervisedLearnerValidationExperiment extends LearnerValidationExperiment<InputOutputPair<InputType,OutputType>,InputOutputPair<InputType,OutputType>,Evaluator<? super InputType,OutputType>,StatisticType,SummaryType> implements Serializable


Package gov.sandia.cognition.learning.function

Class gov.sandia.cognition.learning.function.ConstantEvaluator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

value

Object value
The output value.

Class gov.sandia.cognition.learning.function.LinearCombinationFunction extends AbstractCloneableSerializable implements Serializable

Serialized Fields

basisFunctions

ArrayList<E> basisFunctions
Collection of basis functions to combine to produce the output


coefficients

Vector coefficients
Coefficients for the basisFunctions


Package gov.sandia.cognition.learning.function.categorization

Class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

categories

Set<E> categories
The set of categories that are the possible output values of the categorizer.

Class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer extends LinearBinaryCategorizer implements Serializable

Class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer extends AbstractBinaryCategorizer<InputType> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantCategorizer extends AbstractCategorizer<InputType,CategoryType> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.AbstractThresholdBinaryCategorizer extends AbstractDiscriminantBinaryCategorizer<InputType> implements Serializable

Serialized Fields

threshold

double threshold
Threshold, below which I will return lowValue, above or equal to I will return highValue.

Class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer extends AbstractDiscriminantCategorizer<InputType,CategoryType,Double> implements Serializable

Serialized Fields

categoryPairsToEvaluatorMap

Map<K,V> categoryPairsToEvaluatorMap
Maps false-true category pairs .

Class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,Boolean>>,? extends Evaluator<? super InputType,Boolean>>> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

preprocessor

Evaluator<InputType,OutputType> preprocessor
The preprocessor for the input data.


categorizer

Categorizer<InputType,CategoryType> categorizer
The categorizer.

Class gov.sandia.cognition.learning.function.categorization.DefaultConfidenceWeightedBinaryCategorizer extends AbstractConfidenceWeightedBinaryCategorizer implements Serializable

Serialized Fields

covariance

Matrix covariance
The covariance matrix.

Class gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer extends KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.DiagonalConfidenceWeightedBinaryCategorizer extends AbstractConfidenceWeightedBinaryCategorizer implements Serializable

Serialized Fields

variance

Vector variance
The variance values, which is the diagonal of the covariance matrix. It is stored as a vector to avoid needing to instantiate and use matrix operations with it.

Class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter extends AbstractCategorizer<InputType,CategoryType> implements Serializable

Serialized Fields

evaluator

Evaluator<InputType,OutputType> evaluator
The evaluator that is being wrapped into a categorizer.

Class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>>> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer extends ScalarFunctionToBinaryCategorizerAdapter<Vector> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer.ClosedFormSolver extends AbstractCloneableSerializable implements Serializable

Serialized Fields

defaultCovariance

double defaultCovariance
The default covariance.

Class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer extends AbstractDiscriminantBinaryCategorizer<InputType> implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The internal kernel.


examples

Collection<E> examples
The list of weighted examples that are used for categorization.


bias

double bias
The bias term.

Class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer extends AbstractDiscriminantBinaryCategorizer<Vectorizable> implements Serializable

Serialized Fields

weights

Vector weights
The weight vector.


bias

double bias
The bias term.

Class gov.sandia.cognition.learning.function.categorization.LinearMultiCategorizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

prototypes

Map<K,V> prototypes
A map of each category to its prototype categorizer.

Class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer extends AbstractDistribution<ObservationType> implements Serializable

Serialized Fields

categoryPriors

DataDistribution.PMF<KeyType> categoryPriors
PMF of the various categories


categoryConditionals

Map<K,V> categoryConditionals
Map that contains the probability functions for the observations for the given categories.

Class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer.Learner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

conditionalLearner

BatchLearner<DataType,ResultType> conditionalLearner
Learner that creates the conditional distributions for each category.

Class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter extends AbstractThresholdBinaryCategorizer<InputType> implements Serializable

Serialized Fields

evaluator

Evaluator<InputType,OutputType> evaluator
The scalar evaluator.

Class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer extends AbstractThresholdBinaryCategorizer<Double> implements Serializable

Class gov.sandia.cognition.learning.function.categorization.VectorElementThresholdCategorizer extends AbstractThresholdBinaryCategorizer<Vectorizable> implements Serializable

Serialized Fields

index

int index
The index to apply the threshold to.

Class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer extends AbstractDiscriminantCategorizer<InputType,CategoryType,Double> implements Serializable

Serialized Fields

evaluator

Evaluator<InputType,OutputType> evaluator
The evaluator that outputs a vector to return.

Class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,Vector>>,? extends Evaluator<? super InputType,? extends Vectorizable>>> implements Serializable

Serialized Fields

vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The vector factory used.


Package gov.sandia.cognition.learning.function.cost

Class gov.sandia.cognition.learning.function.cost.AbstractCostFunction extends AbstractCloneableSerializable implements Serializable

Serialized Fields

costParameters

Object costParameters
The parameters of the cost function.

Class gov.sandia.cognition.learning.function.cost.AbstractParallelizableCostFunction extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable

Class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction extends AbstractSupervisedPerformanceEvaluator<InputType,TargetType,TargetType,Double> implements Serializable

Serialized Fields

costParameters

Collection<E> costParameters
Labeled dataset to use to evaluate the cost against

Class gov.sandia.cognition.learning.function.cost.ClusterDistortionMeasure extends AbstractCloneableSerializable implements Serializable

Serialized Fields

costParameters

ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> costParameters
Divergence function that defines the cost function

Class gov.sandia.cognition.learning.function.cost.EuclideanDistanceCostFunction extends AbstractCloneableSerializable implements Serializable

Serialized Fields

goal

Vector goal
The goal of the cost function.

Class gov.sandia.cognition.learning.function.cost.KolmogorovSmirnovDivergence extends AbstractCostFunction<UnivariateDistribution<DataType extends Number>,Collection<? extends DataType extends Number>> implements Serializable

Class gov.sandia.cognition.learning.function.cost.MeanL1CostFunction extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable

Class gov.sandia.cognition.learning.function.cost.MeanSquaredErrorCostFunction extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable

Class gov.sandia.cognition.learning.function.cost.NegativeLogLikelihood extends AbstractCostFunction<ComputableDistribution<DataType>,Collection<? extends DataType>> implements Serializable

Class gov.sandia.cognition.learning.function.cost.ParallelClusterDistortionMeasure extends ClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> implements Serializable

Class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable

Serialized Fields

costFunction

ParallelizableCostFunction costFunction
Cost function to parallelize

Class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood extends NegativeLogLikelihood<DataType> implements Serializable

Class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction extends AbstractParallelizableCostFunction implements Serializable

Class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.Cache extends AbstractCloneableSerializable implements Serializable

Serialized Fields

J

Matrix J
Jacobian


JtJ

Matrix JtJ
Inner-product of the Jacobian matrix: J.transpose().times( J )


Jte

Vector Jte
Jacobian transpose times Error: J.transpose().times( error )


parameterCost

double parameterCost
Cost-function value of the parameter set

Class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.GradientPartialSSE extends DefaultPair<Vector,Double> implements Serializable


Package gov.sandia.cognition.learning.function.distance

Class gov.sandia.cognition.learning.function.distance.ChebyshevDistanceMetric extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.distance.CosineDistanceMetric extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

divergenceFunction

DivergenceFunction<FirstType,SecondType> divergenceFunction
The internal divergence function for the object to use.

Class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator extends DefaultVectorFactoryContainer implements Serializable

Serialized Fields

divergenceFunction

DivergenceFunction<FirstType,SecondType> divergenceFunction
The divergence function to apply between the data and the input.


values

Collection<E> values
The data to evaluate the divergence from.

Class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super DataType,? extends Collection<ValueType>>> implements Serializable

Serialized Fields

divergenceFunction

DivergenceFunction<FirstType,SecondType> divergenceFunction
The divergence function to apply between the data and the input.


vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The vector factory to use.

Class gov.sandia.cognition.learning.function.distance.EuclideanDistanceMetric extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.distance.EuclideanDistanceSquaredMetric extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.distance.IdentityDistanceMetric extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.distance.ManhattanDistanceMetric extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.distance.MinkowskiDistanceMetric extends AbstractCloneableSerializable implements Serializable

Serialized Fields

power

double power
The power that the distance is computed to.

Class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric extends AbstractCloneableSerializable implements Serializable

Serialized Fields

weights

Vector weights
The weights assigned to each dimension for the distance. The weights cannot be negative.


Package gov.sandia.cognition.learning.function.kernel

Class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

kernel

Kernel<InputType> kernel
The internal kernel.

Class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

kernels

Collection<E> kernels
The collection of kernels in the container.

Class gov.sandia.cognition.learning.function.kernel.ExponentialKernel extends DefaultKernelContainer<InputType> implements Serializable

Class gov.sandia.cognition.learning.function.kernel.KernelDistanceMetric extends DefaultKernelContainer<InputType> implements Serializable

Class gov.sandia.cognition.learning.function.kernel.LinearKernel extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.kernel.NormalizedKernel extends DefaultKernelContainer<InputType> implements Serializable

Class gov.sandia.cognition.learning.function.kernel.PolynomialKernel extends AbstractCloneableSerializable implements Serializable

Serialized Fields

degree

int degree
The degree of the polynomial. Must be positive.


constant

double constant
The constant for the polynomial.

Class gov.sandia.cognition.learning.function.kernel.ProductKernel extends DefaultKernelsContainer<InputType> implements Serializable

Class gov.sandia.cognition.learning.function.kernel.RadialBasisKernel extends AbstractCloneableSerializable implements Serializable

Serialized Fields

sigma

double sigma
Sigma is the parameter that controls the bandwidth of the radial basis kernel.


negativeTwoSigmaSquared

double negativeTwoSigmaSquared
This value is cached so it doesn't have to be computed each time. It is -2.0 * sigma * sigma.

Class gov.sandia.cognition.learning.function.kernel.ScalarFunctionKernel extends AbstractCloneableSerializable implements Serializable

Serialized Fields

function

Evaluator<InputType,OutputType> function
The scalar function for the kernel to use.

Class gov.sandia.cognition.learning.function.kernel.SigmoidKernel extends AbstractCloneableSerializable implements Serializable

Serialized Fields

kappa

double kappa
The kappa value to multiply times the dot product.


constant

double constant
The constant used in the sigmoid.

Class gov.sandia.cognition.learning.function.kernel.SumKernel extends DefaultKernelsContainer<InputType> implements Serializable

Class gov.sandia.cognition.learning.function.kernel.VectorFunctionKernel extends DefaultKernelContainer<Vector> implements Serializable

Serialized Fields

function

VectorFunction function
The vector function to use.

Class gov.sandia.cognition.learning.function.kernel.WeightedKernel extends DefaultKernelContainer<InputType> implements Serializable

Serialized Fields

weight

double weight
The weight on the kernel. Must be non-negative.

Class gov.sandia.cognition.learning.function.kernel.ZeroKernel extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.function.regression

Class gov.sandia.cognition.learning.function.regression.AbstractRegressor extends AbstractScalarFunction<InputType> implements Serializable


Package gov.sandia.cognition.learning.function.scalar

Class gov.sandia.cognition.learning.function.scalar.AtanFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Serialized Fields

scaleFactor

double scaleFactor
Scales the Math.atan() value to ensure that it has the desired "maxMagnitude"

Class gov.sandia.cognition.learning.function.scalar.CosineFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Serialized Fields

amplitude

double amplitude
Maximum value of the cosine function. The value of "A" in y=A*cos(2*pi*f*x + phase).


frequency

double frequency
Frequency of the cosine function. The value of "f" in y=A*cos(2*pi*f*x + phase).


phase

double phase
Phase of the cosine function. The value of "phase" in y=A*cos(2*pi*f*x + phase).

Class gov.sandia.cognition.learning.function.scalar.IdentityScalarFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction extends DefaultKernelContainer<InputType> implements Serializable

Serialized Fields

examples

Collection<E> examples
The list of weighted examples that are used for categorization.


bias

double bias
The bias term.

Class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator extends AbstractStatefulEvaluator<Double,Double,FiniteCapacityBuffer<Double>> implements Serializable

Serialized Fields

cdf

CumulativeDistributionFunction<NumberType extends Number> cdf
The cumulative distribution function to base the evaluator on.


capacity

int capacity
The capacity of the state.

Class gov.sandia.cognition.learning.function.scalar.LinearCombinationScalarFunction extends LinearCombinationFunction<InputType,Double> implements Serializable

Class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant extends AbstractRegressor<Vectorizable> implements Serializable

Serialized Fields

weightVector

Vector weightVector
Weight Vector to dot-product with the input

Class gov.sandia.cognition.learning.function.scalar.LinearDiscriminantWithBias extends LinearDiscriminant implements Serializable

Serialized Fields

bias

double bias
Bias term that gets added to the output of the dot product.

Class gov.sandia.cognition.learning.function.scalar.LinearFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Serialized Fields

slope

double slope
The slope (m).


offset

double offset
The offset (b).

Class gov.sandia.cognition.learning.function.scalar.LinearVectorScalarFunction extends AbstractRegressor<Vectorizable> implements Serializable

Serialized Fields

weights

Vector weights
The weight vector.


bias

double bias
The bias term.

Class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction extends KernelScalarFunction<InputType> implements Serializable

Serialized Fields

constantWeight

double constantWeight
The constant weight is used as a weight for the constant value that is added to the result to bias the function to the constant value.


constantValue

double constantValue
The constant value is what the constant weight biases the function toward when there is near zero weight.

Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Serialized Fields

exponent

double exponent
Real-valued exponent of this polynomial

Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic extends PolynomialFunction.Quadratic implements Serializable

Serialized Fields

q3

double q3
Cubic (third-order) coefficient

Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Serialized Fields

q0

double q0
Constant (zeroth-order) coefficient


q1

double q1
Linear (first-order) coefficient

Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic extends PolynomialFunction.Linear implements Serializable

Serialized Fields

q2

double q2
Quadratic (second-order) coefficient

Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Regression extends AbstractCloneableSerializable implements Serializable

Serialized Fields

polynomials

ScalarBasisSet<InputType> polynomials
Polynomials to use in the regression

Class gov.sandia.cognition.learning.function.scalar.SigmoidFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable

Class gov.sandia.cognition.learning.function.scalar.ThresholdFunction extends AbstractUnivariateScalarFunction implements Serializable

Serialized Fields

highValue

double highValue
Values above (or equal to) threshold are assigned this value


lowValue

double lowValue
Values below threshold are assigned this value


threshold

double threshold
Current threshold, below which a value is assigned lowValue, above which (or equal to) is assigned highValue

Class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction extends AbstractScalarFunction<Vectorizable> implements Serializable

Serialized Fields

index

int index
The index of the vector to get.

Class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant extends AbstractRegressor<InputType> implements Serializable

Serialized Fields

vectorFunction

Evaluator<InputType,OutputType> vectorFunction
Maps the input space to a Vector


discriminant

LinearDiscriminant discriminant
The dot product of the discriminant with the output of the vectorFunction is the output (scalar) value. Must have the same dimensions as the outputDimensionality of vectorFunction.

Class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction extends AbstractRegressor<InputType> implements Serializable

Serialized Fields

vectorFunction

Evaluator<InputType,OutputType> vectorFunction
The function that takes a given input and outputs a 1-dimensional vector.

Class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction.Learner extends AbstractCloneableSerializable implements Serializable

Serialized Fields

vectorLearner

BatchLearner<DataType,ResultType> vectorLearner
The supervised learner that learns on vectors as outputs.


Package gov.sandia.cognition.learning.function.summarizer

Class gov.sandia.cognition.learning.function.summarizer.MostFrequentSummarizer extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.learning.function.vector

Class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork extends FeedforwardNeuralNetwork implements Serializable

Class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel extends GeneralizedLinearModel implements Serializable

Class gov.sandia.cognition.learning.function.vector.ElementWiseDifferentiableVectorFunction extends ElementWiseVectorFunction implements Serializable

Class gov.sandia.cognition.learning.function.vector.ElementWiseVectorFunction extends AbstractCloneableSerializable implements Serializable

Serialized Fields

scalarFunction

UnivariateScalarFunction scalarFunction
Underlying scalar function to apply to each Vector element

Class gov.sandia.cognition.learning.function.vector.EntropyEvaluator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.function.vector.FeedforwardNeuralNetwork extends AbstractCloneableSerializable implements Serializable

Serialized Fields

layers

ArrayList<E> layers
Layers that comprise this neural network

Class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

gaussianMixture

MixtureOfGaussians.PDF gaussianMixture
Underlying MixtureOfGaussians that computes context probabilities

Class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer.Learner extends AnytimeAlgorithmWrapper<GaussianContextRecognizer,AnytimeBatchLearner<Collection<? extends Vector>,Collection<GaussianCluster>>> implements Serializable

Class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel extends AbstractCloneableSerializable implements Serializable

Serialized Fields

discriminant

MultivariateDiscriminant discriminant
GradientDescendable that multiplies an input by the internal matrix


squashingFunction

VectorFunction squashingFunction
VectorFunction that is applied to the output of the matrix multiply

Class gov.sandia.cognition.learning.function.vector.LinearCombinationVectorFunction extends LinearCombinationFunction<Vector,Vector> implements Serializable

Class gov.sandia.cognition.learning.function.vector.LinearVectorFunction extends AbstractCloneableSerializable implements Serializable

Serialized Fields

scaleFactor

double scaleFactor
Scales the input by this amount.

Class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant extends AbstractCloneableSerializable implements Serializable

Serialized Fields

discriminant

Matrix discriminant
Internal matrix to premultiply input vectors by.

Class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias extends MultivariateDiscriminant implements Serializable

Serialized Fields

bias

Vector bias
Bias term that gets added the output of the matrix multiplication.

Class gov.sandia.cognition.learning.function.vector.ScalarBasisSet extends AbstractCloneableSerializable implements Serializable

Serialized Fields

basisFunctions

Collection<E> basisFunctions
Collection of scalar basis functions, where the ith function operates on the ith element of the output Vector

Class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator extends DefaultVectorFactoryContainer implements Serializable

Serialized Fields

inputDimensionality

int inputDimensionality
The expected dimensionality of the input. All the subIndices must be less than this value.


subIndices

int[] subIndices
The indices to pull out of an input vector to create a new vector from.

Class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork extends AbstractRandomized implements Serializable

Serialized Fields

inputToHiddenWeights

Matrix inputToHiddenWeights
Matrix of weights to pre-multiply the inputs by.


inputToHiddenBiasWeights

Vector inputToHiddenBiasWeights
Bias weights to add to each of the hidden units.


hiddenToOutputWeights

Matrix hiddenToOutputWeights
Matrix of weights to pre-multiply the hidden-unit activations by.


hiddenToOutputBiasWeights

Vector hiddenToOutputBiasWeights
Bias weights to add to each of the output units.


squashingFunction

DifferentiableUnivariateScalarFunction squashingFunction
Squashing function to apply at the hidden layer.


initializationRange

double initializationRange
Range of values to initialize the weights between, must be greater than or equal to zero.

Class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverter extends Object implements Serializable

Class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverterWithBias extends VectorizableVectorConverter implements Serializable

Serialized Fields

vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The factory used to create the vector.


Package gov.sandia.cognition.learning.parameter

Class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper extends AbstractBatchLearnerContainer<LearnerType extends BatchLearner<? super DataType,? extends ResultType>> implements Serializable

Serialized Fields

parameterAdapters

LinkedList<E> parameterAdapters
The list of parameter adapters for the learner. It should be null if there are no adapters.


Package gov.sandia.cognition.learning.performance

Class gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.performance.MeanAbsoluteErrorEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,Double,Double,Double> implements Serializable

Class gov.sandia.cognition.learning.performance.MeanSquaredErrorEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,Double,Double,Double> implements Serializable

Class gov.sandia.cognition.learning.performance.MeanZeroOneErrorEvaluator extends AbstractSupervisedCostFunction<InputType,DataType> implements Serializable

Class gov.sandia.cognition.learning.performance.RootMeanSquaredErrorEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,Double,Double,Double> implements Serializable


Package gov.sandia.cognition.learning.performance.categorization

Class gov.sandia.cognition.learning.performance.categorization.AbstractBinaryConfusionMatrix extends AbstractConfusionMatrix<Boolean> implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.ConfusionMatrixPerformanceEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,CategoryType,CategoryType,ConfusionMatrix<CategoryType>> implements Serializable

Serialized Fields

factory

Factory<CreatedType> factory
The factory used to create the confusion matrix of the evaluator.

Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix extends AbstractBinaryConfusionMatrix implements Serializable

Serialized Fields

trueNegativesCount

double trueNegativesCount
Number of true negatives. The (false, false) entry.


falsePositivesCount

double falsePositivesCount
Number of false positives. The (false, true) entry.


falseNegativesCount

double falseNegativesCount
Number of false negatives. The (true, false) entry.


truePositivesCount

double truePositivesCount
Number of true positives. The (true, true) entry.

Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.CombineSummarizer extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.PerformanceEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,Boolean,Boolean,DefaultBinaryConfusionMatrix> implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval.Summary extends AbstractCloneableSerializable implements Serializable

Serialized Fields

confidence

double confidence
The confidence for the created interval.

Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix extends AbstractConfusionMatrix<CategoryType> implements Serializable

Serialized Fields

confusions

Map<K,V> confusions
The backing map of confusion matrix entries. The first key is the actual category and the second is the predicted category.

Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.ActualPredictedPairSummarizer extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.CombineSummarizer extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.Factory extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.math

Class gov.sandia.cognition.math.AbstractDifferentiableUnivariateScalarFunction extends AbstractUnivariateScalarFunction implements Serializable

Class gov.sandia.cognition.math.AbstractEuclideanRing extends AbstractRing<RingType extends EuclideanRing<RingType>> implements Serializable

Class gov.sandia.cognition.math.AbstractField extends AbstractEuclideanRing<FieldType extends Field<FieldType>> implements Serializable

Class gov.sandia.cognition.math.AbstractRing extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.AbstractScalarFunction extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.AbstractUnivariateScalarFunction extends AbstractScalarFunction<Double> implements Serializable

Class gov.sandia.cognition.math.ComplexNumber extends AbstractField<ComplexNumber> implements Serializable

Serialized Fields

realPart

double realPart
The real part of the ComplexNumber


imaginaryPart

double imaginaryPart
The imaginary part of the ComplexNumber

Class gov.sandia.cognition.math.LentzMethod extends AbstractAnytimeAlgorithm<Double> implements Serializable

Serialized Fields

tolerance

double tolerance
Tolerance of the algorithm for convergence


minDenominator

double minDenominator
Value to keep denominators from equaling 0.0


currentC

double currentC
Current value of the "C" variable in Lentz's method


currentD

double currentD
Current value of the "D" variable in Lentz's method


result

Double result
Value of the continued fraction, null if not valid


fractionValue

double fractionValue
Running (intermediate) value of the fraction value


keepGoing

boolean keepGoing
Flag to keep going or stop

Class gov.sandia.cognition.math.LogNumber extends Number implements Serializable

Serialized Fields

negative

boolean negative
The sign of the value, sign(value). True for negative, and false for positive.


logValue

double logValue
The log of the absolute value represented by this object, log(|value|).

Class gov.sandia.cognition.math.MutableDouble extends Number implements Serializable

serialVersionUID: 20110131L

Serialized Fields

value

double value
The value. Note: This is public just for performance reasons when people don't want to do the getter/setter for overhead reasons.

Class gov.sandia.cognition.math.MutableInteger extends Number implements Serializable

serialVersionUID: 20110601L

Serialized Fields

value

int value
The value. Note: This is public just for performance reasons when people don't want to do the getter/setter for overhead reasons.

Class gov.sandia.cognition.math.MutableLong extends Number implements Serializable

serialVersionUID: 20110602L

Serialized Fields

value

long value
The value. Note: This is public just for performance reasons when people don't want to do the getter/setter for overhead reasons.

Class gov.sandia.cognition.math.NumberAverager extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.OperationNotConvergedException extends RuntimeException implements Serializable

Class gov.sandia.cognition.math.RingAverager extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.UnivariateSummaryStatistics extends AbstractCloneableSerializable implements Serializable

Serialized Fields

min

double min
Min


max

double max
Max


quintiles

double[] quintiles
Quintile boundaries


confidenceLower

double confidenceLower
Lower 95% confidence region (alpha=0.025)


confidenceUpper

double confidenceUpper
Upper 95% confidence region (alpha=0.975)


median

double median
Median


numSamples

int numSamples
Number of samples


mean

double mean
Arithmetic mean


variance

double variance
Variance


skewness

double skewness
Skew


kurtosis

double kurtosis
Excess kurtosis

Class gov.sandia.cognition.math.UnsignedLogNumber extends Number implements Serializable

Serialized Fields

logValue

double logValue
The log of the value represented by this object, log(value).

Class gov.sandia.cognition.math.WeightedNumberAverager extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.WeightedRingAverager extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.math.geometry

Class gov.sandia.cognition.math.geometry.KDTree extends AbstractCollection<PairType extends Pair<? extends VectorType,DataType>> implements Serializable

Serialized Fields

num

int num
Number of elements in this subtree.


value

Pair<FirstType,SecondType> value
VectorType,DataType value for this node of the subtree.


parent

KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> parent
Parent of this node of the subtree.


leftChild

KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> leftChild
Left child of this subtree


rightChild

KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> rightChild
Right child of this subtree.


comparator

KDTree.PairFirstVectorizableIndexComparator comparator
Comparator of this node to determine less than, greater than, or equality.

Class gov.sandia.cognition.math.geometry.KDTree.Neighborhood.Neighbor extends AbstractCloneableSerializable implements Serializable

Serialized Fields

pair

Pair<FirstType,SecondType> pair
Pair to store.


distance

double distance
Distance associated with this value.

Class gov.sandia.cognition.math.geometry.KDTree.PairFirstVectorizableIndexComparator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

comparator

VectorizableIndexComparator comparator
Embedded comparator for the Vectorizable argument.

Class gov.sandia.cognition.math.geometry.Quadtree extends AbstractCloneableSerializable implements Serializable

Serialized Fields

splitThreshold

int splitThreshold
The minimum number of items allowed in a leaf node. If there are more than this, then a node must be split. This number must be greater than zero.


items

LinkedList<E> items
All of the items in the tree. It should never be null.


initalBounds

Rectangle2D.Double initalBounds
The initial bounds for the tree. This may be null if they are not specified.


root

Quadtree.Node root
The root node of the tree. It should never be null.

Class gov.sandia.cognition.math.geometry.Quadtree.Node extends AbstractCloneableSerializable implements Serializable

Serialized Fields

parent

Quadtree.Node parent
The parent of this node in the tree. Null only for the root node.


bounds

Rectangle2D.Double bounds
The two-dimensional bounds for this node. This is only null if it is the root node and has no elements and no default bounds.


depth

int depth
The depth of this node in the tree.


localItems

LinkedList<E> localItems
The local items stored at this node.


lowerRight

Quadtree.Node lowerRight
The child for the lower-right quadrant of this node.


lowerLeft

Quadtree.Node lowerLeft
The child for the lower-left quadrant of this node.


upperLeft

Quadtree.Node upperLeft
The child for the upper-left quadrant of this node.


upperRight

Quadtree.Node upperRight
The child for the upper-right quadrant of this node.


children

ArrayList<E> children
The list of children for this node. Null to indicate that it has no children and thus is a leaf node.


Package gov.sandia.cognition.math.matrix

Class gov.sandia.cognition.math.matrix.AbstractMatrix extends AbstractRing<Matrix> implements Serializable

Class gov.sandia.cognition.math.matrix.AbstractVector extends AbstractVectorSpace<Vector,VectorEntry> implements Serializable

Class gov.sandia.cognition.math.matrix.AbstractVectorSpace extends AbstractRing<VectorType extends VectorSpace<VectorType,? extends EntryType>> implements Serializable

Class gov.sandia.cognition.math.matrix.DefaultInfiniteVector extends AbstractMutableDoubleMap<KeyType> implements Serializable

Class gov.sandia.cognition.math.matrix.DefaultVectorFactoryContainer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

vectorFactory

VectorFactory<VectorType extends Vector> vectorFactory
The vector factory used to create new vectors.

Class gov.sandia.cognition.math.matrix.DimensionalityMismatchException extends RuntimeException implements Serializable

Class gov.sandia.cognition.math.matrix.MatrixFactory extends Object implements Serializable

Class gov.sandia.cognition.math.matrix.NumericalDifferentiator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

delta

double delta
Value for x-value differencing, must be greater than 0.0


internalFunction

Evaluator<InputType,OutputType> internalFunction
Internal function to numerically differencing.

Class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian extends NumericalDifferentiator<Double,Double,Double> implements Serializable

Class gov.sandia.cognition.math.matrix.NumericalDifferentiator.MatrixJacobian extends NumericalDifferentiator<Vector,Vector,Matrix> implements Serializable

Class gov.sandia.cognition.math.matrix.NumericalDifferentiator.VectorJacobian extends NumericalDifferentiator<Vector,Double,Vector> implements Serializable

Class gov.sandia.cognition.math.matrix.SparseVectorFactory extends VectorFactory<VectorType extends Vector> implements Serializable

Class gov.sandia.cognition.math.matrix.VectorFactory extends Object implements Serializable

Class gov.sandia.cognition.math.matrix.VectorizableIndexComparator extends AbstractCloneableSerializable implements Serializable

Serialized Fields

index

int index
Index to compare against.


Package gov.sandia.cognition.math.matrix.decomposition

Class gov.sandia.cognition.math.matrix.decomposition.EigenvectorPowerIteration extends AbstractCloneableSerializable implements Serializable


Package gov.sandia.cognition.math.matrix.mtj

Class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix extends AbstractMatrix implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector extends AbstractVector implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix extends AbstractMTJMatrix implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.DenseMatrix extends AbstractMTJMatrix implements Serializable

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
                        ClassNotFoundException
Reads in a serialized class from the specified stream

Throws:
IOException - On bad read
ClassNotFoundException - if next object isn't DenseMatrix

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException
Writes a DenseMatrix out to a serialized file

Throws:
IOException - On bad write

Class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ extends MatrixFactory<DenseMatrix> implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.DenseVector extends AbstractMTJVector implements Serializable

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
                        ClassNotFoundException
Reads in a serialized class from the specified stream

Throws:
IOException - On bad read
ClassNotFoundException - if next object isn't DenseVector

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException
Writes a DenseVector out to a serialized stream (usually file)

Throws:
IOException - On bad write

Class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ extends VectorFactory<DenseVector> implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ extends MatrixFactory<DiagonalMatrixMTJ> implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ extends AbstractMTJMatrix implements Serializable

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
                        ClassNotFoundException
Reads in a serialized class from the specified stream

Throws:
IOException - On bad read
ClassNotFoundException - if next object isn't DenseMatrix

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException
Writes a DenseMatrix out to a serialized file

Throws:
IOException - On bad write

Class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix extends AbstractSparseMatrix implements Serializable

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
                        ClassNotFoundException
Custom deserialization is needed.

Throws:
IOException - If there is an error with the stream.
ClassNotFoundException - If a class used by this one cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException
Custom serialization is needed.

Throws:
IOException - If there is an error writing to the stream.

Class gov.sandia.cognition.math.matrix.mtj.SparseMatrix extends SparseRowMatrix implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ extends MatrixFactory<SparseMatrix> implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix extends AbstractSparseMatrix implements Serializable

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
                        ClassNotFoundException
Custom deserialization is needed.

Throws:
IOException - If there is an error with the stream.
ClassNotFoundException - If a class used by this one cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException
Custom serialization is needed.

Throws:
IOException - If there is an error writing to the stream.

Class gov.sandia.cognition.math.matrix.mtj.SparseVector extends AbstractMTJVector implements Serializable

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
                        ClassNotFoundException
This method provides custom deserialization for the class since the MTJ class does not implement Serializable.

Throws:
IOException - If there is an error reading the object.
ClassNotFoundException - If a class cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException
This method provides custom serialization for the class since the MTJ class does not implement Serializable.

Throws:
IOException - If there is an error with the stream.

Class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ extends SparseVectorFactory<SparseVector> implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.Vector1 extends DenseVector implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.Vector2 extends DenseVector implements Serializable

Class gov.sandia.cognition.math.matrix.mtj.Vector3 extends DenseVector implements Serializable


Package gov.sandia.cognition.math.matrix.mtj.decomposition

Class gov.sandia.cognition.math.matrix.mtj.decomposition.CholeskyDecompositionMTJ extends AbstractCloneableSerializable implements Serializable

Serialized Fields

R

DenseMatrix R
Cholesky factor, such that R.transpose().times( R ) equals the original matrix


Package gov.sandia.cognition.math.signals

Class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter extends AbstractStatefulEvaluator<Double,Double,DefaultPair<FiniteCapacityBuffer<Double>,FiniteCapacityBuffer<Double>>> implements Serializable

Serialized Fields

movingAverageCoefficients

Vector movingAverageCoefficients
Coefficients of the moving-average filter. Element 0 is applied to the most-recent input, Element 1 is applied to the second-most-recent, and so forth. The dimensionality of the Vector is the order of the filter.


autoRegressiveCoefficients

Vector autoRegressiveCoefficients
Coefficients of the autoregressive filter. Element 0 is applied to the most-recent output, Element 1 is applied to the second-most-recent, and so forth. The dimensionality of the Vector is the order of the filter.

Class gov.sandia.cognition.math.signals.FourierTransform extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.signals.FourierTransform.Inverse extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.math.signals.LinearDynamicalSystem extends AbstractStatefulEvaluator<Vector,Vector,Vector> implements Serializable

Serialized Fields

A

Matrix A
System (Jacobian) matrix. Must be square.


B

Matrix B
Input-gain matrix. Columns must equal A's rows.


C

Matrix C
Output-selector matrix. Columns must equal A's rows.

Class gov.sandia.cognition.math.signals.MovingAverageFilter extends AbstractStatefulEvaluator<Double,Double,FiniteCapacityBuffer<Double>> implements Serializable

Serialized Fields

movingAverageCoefficients

Vector movingAverageCoefficients
Coefficients of the moving-average filter. Element 0 is applied to the most-recent input, Element 1 is applied to the second-most-recent, and so forth. The dimensionality of the Vector is the order of the filter.

Class gov.sandia.cognition.math.signals.PIDController extends AbstractStatefulEvaluator<Double,Double,PIDController.State> implements Serializable

Serialized Fields

targetInput

double targetInput
Set point target to achieve at steady-state.


proportionalGain

double proportionalGain
Proportional-error gain.


integralGain

double integralGain
Integral-error gain.


derivativeGain

double derivativeGain
Derivative-error gain.

Class gov.sandia.cognition.math.signals.PIDController.State extends AbstractCloneableSerializable implements Serializable

Serialized Fields

lastErr

double lastErr
Last error.


errSum

double errSum
Sum of all errors.


Package gov.sandia.cognition.statistics

Class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution extends AbstractClosedFormUnivariateDistribution<Double> implements Serializable

Class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution extends AbstractDistribution<NumberType extends Number> implements Serializable

Class gov.sandia.cognition.statistics.AbstractDataDistribution extends AbstractMutableDoubleMap<KeyType> implements Serializable

Class gov.sandia.cognition.statistics.AbstractDistribution extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.statistics.AbstractIncrementalEstimator extends AbstractBatchAndIncrementalLearner<DataType,SufficientStatisticsType extends SufficientStatistic<DataType,DistributionType>> implements Serializable

Class gov.sandia.cognition.statistics.AbstractRandomVariable extends AbstractRing<RandomVariable<DataType>> implements Serializable

Class gov.sandia.cognition.statistics.AbstractSufficientStatistic extends AbstractCloneableSerializable implements Serializable

Serialized Fields

count

long count
Number of data points used to create this SufficientStatistic

Class gov.sandia.cognition.statistics.DefaultDistributionParameter extends AbstractNamed implements Serializable

Serialized Fields

conditionalDistribution

ClosedFormDistribution<DataType> conditionalDistribution
Distribution from which to pull the parameters.

Class gov.sandia.cognition.statistics.UnivariateRandomVariable extends AbstractRandomVariable<Number> implements Serializable

Serialized Fields

numSamples

int numSamples
Number of samples to draw from the distribution to perform the empirical algebra approximation.


random

Random random
Random number generator used for sampling the distribution.


distribution

UnivariateDistribution<NumberType extends Number> distribution
Scalar distribution that backs the random variable, from which samples will be drawn to approximate the distribution during algebra.


Package gov.sandia.cognition.statistics.bayesian

Class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter extends AbstractNamed implements Serializable

Serialized Fields

conditionalDistribution

ClosedFormDistribution<DataType> conditionalDistribution
Distribution from which to pull the parameters.


parameterPrior

Distribution<DataType> parameterPrior
Distribution of values that the parameter is assumed to take.

Class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter extends AbstractBatchAndIncrementalLearner<Vector,MultivariateGaussian> implements Serializable

Serialized Fields

currentInput

Vector currentInput
Current input to the model.


modelCovariance

Matrix modelCovariance
Covariance associated with the system's model.


measurementCovariance

Matrix measurementCovariance
Covariance associated with the measurements.

Class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo extends AbstractAnytimeBatchLearner<Collection<? extends ObservationType>,DataDistribution<ParameterType>> implements Serializable

Serialized Fields

random

Random random
Random number generator.


burnInIterations

int burnInIterations
The number of iterations that must transpire before the algorithm begins collection the samples.


iterationsPerSample

int iterationsPerSample
The number of iterations that must transpire between capturing samples from the distribution.


currentParameter

Object currentParameter
The current parameters in the random walk.


previousParameter

Object previousParameter
The previous parameter in the random walk.

Class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter extends AbstractBatchAndIncrementalLearner<ObservationType,DataDistribution<ParameterType>> implements Serializable

Serialized Fields

updater

ParticleFilter.Updater<ObservationType,ParameterType> updater
Updates the particle given an existing particle.


numParticles

int numParticles
Number of particles in the filter.

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling extends AbstractCloneableSerializable implements Serializable

Serialized Fields

logFunction

AdaptiveRejectionSampling.LogEvaluator<EvaluatorType extends Evaluator<Double,Double>> logFunction
Logarithm of the function that we want to evaluate


points

ArrayList<E> points
Input-output point pairs, sorted in ascending order by their x-axis value


maxNumPoints

int maxNumPoints
Maximum number of points that will be stored


minSupport

double minSupport
Minimum support (x-value) of the logFunction


maxSupport

double maxSupport
Maximum support (x-value) of the logFunction


upperEnvelope

AdaptiveRejectionSampling.UpperEnvelope upperEnvelope
Upper envelope of the logFunction


lowerEnvelope

AdaptiveRejectionSampling.LowerEnvelope lowerEnvelope
Lower envelope of the logFunction

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.AbstractEnvelope extends AbstractUnivariateScalarFunction implements Serializable

Serialized Fields

lines

ArrayList<E> lines
Line segments that comprise the envelope

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LineSegment extends PolynomialFunction.Linear implements Serializable

Serialized Fields

left

double left
Left (minimum) x-axis value


right

double right
Right (maximum) x-axis value

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LogEvaluator extends AbstractUnivariateScalarFunction implements Serializable

Serialized Fields

function

Evaluator<InputType,OutputType> function
Evaluator to wrap and compute the natural logarithm of.

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LowerEnvelope extends AdaptiveRejectionSampling.AbstractEnvelope implements Serializable

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.PDFLogEvaluator extends AdaptiveRejectionSampling.LogEvaluator<ProbabilityFunction<Double>> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.Point extends DefaultInputOutputPair<Double,Double> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope extends AdaptiveRejectionSampling.AbstractEnvelope implements Serializable

Serialized Fields

segmentCDF

double[] segmentCDF
Cumulative sums of the normalized weights of the lines... This is automatically computed by computeSegments method.

Class gov.sandia.cognition.statistics.bayesian.BayesianCredibleInterval extends ConfidenceInterval implements Serializable

Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression extends AbstractCloneableSerializable implements Serializable

Serialized Fields

outputVariance

double outputVariance
Assumed known variance of the outputs (measurements), must be greater than zero.


weightPrior

MultivariateGaussian weightPrior
Prior distribution of the weights, typically a zero-mean, diagonal-variance distribution.

Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator extends BayesianLinearRegression implements Serializable

Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator.SufficientStatistic extends AbstractSufficientStatistic<InputOutputPair<? extends Vectorizable,Double>,MultivariateGaussian> implements Serializable

Serialized Fields

z

Vector z
"z" statistic, proportional to the mean


covarianceInverse

Matrix covarianceInverse
Covariance inverse, sometimes called "precision"

Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.PredictiveDistribution extends AbstractCloneableSerializable implements Serializable

Serialized Fields

posterior

MultivariateGaussian posterior
Posterior distribution of the weights given the data.

Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression extends AbstractCloneableSerializable implements Serializable

Serialized Fields

weightPrior

MultivariateGaussian weightPrior
Prior distribution of the weights, typically a zero-mean, diagonal-variance distribution.


outputVariance

InverseGammaDistribution outputVariance
Distribution of the output (measurement) variance

Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator extends BayesianRobustLinearRegression implements Serializable

Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic extends AbstractSufficientStatistic<InputOutputPair<? extends Vectorizable,Double>,MultivariateGaussianInverseGammaDistribution> implements Serializable

Serialized Fields

outputSumSquared

double outputSumSquared
Sum of the output squared


z

Vector z
"z" statistic, proportional to the mean


covarianceInverse

Matrix covarianceInverse
Covariance inverse, sometimes called "precision"

Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.PredictiveDistribution extends AbstractCloneableSerializable implements Serializable

Serialized Fields

posterior

MultivariateGaussianInverseGammaDistribution posterior
Posterior distribution of the weights given the data.

Class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter extends DefaultDistributionParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>> implements Serializable

Serialized Fields

parameterPrior

Distribution<DataType> parameterPrior
Distribution of values that the parameter is assumed to take.

Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel extends AbstractMarkovChainMonteCarlo<ObservationType,DirichletProcessMixtureModel.Sample<ObservationType>> implements Serializable

Serialized Fields

updater

DirichletProcessMixtureModel.Updater<ObservationType> updater
Creates the clusters and predictive prior distributions


numInitialClusters

int numInitialClusters
Number of clusters to initialize


reestimateAlpha

boolean reestimateAlpha
Flag to automatically re-estimate the alpha parameter


initialAlpha

double initialAlpha
Initial value of alpha, the concentration parameter of the Dirichlet Process

Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMCluster extends DefaultCluster<ObservationType> implements Serializable

Serialized Fields

probabilityFunction

ProbabilityFunction<DataType> probabilityFunction
Probability function describing the assigned data

Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMLogConditional extends AbstractCloneableSerializable implements Serializable

Serialized Fields

logConditional

double logConditional
log conditional likelihood

Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater extends AbstractCloneableSerializable implements Serializable

Serialized Fields

estimator

MultivariateGaussianMeanCovarianceBayesianEstimator estimator
Bayesian estimator for the parameters

Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanUpdater extends AbstractCloneableSerializable implements Serializable

Serialized Fields

estimator

MultivariateGaussianMeanBayesianEstimator estimator
Bayesian estimator for the parameters

Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample extends AbstractCloneableSerializable implements Serializable

Serialized Fields

alpha

double alpha
Scaling parameter which defines the strength of the base distribution, must be greater than zero.


clusters

ArrayList<E> clusters
Point mass realizations from the base distribution.


posteriorLogLikelihood

Double posteriorLogLikelihood
Posterior log likelihood of the sample

Class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter extends AbstractKalmanFilter implements Serializable

Serialized Fields

motionModel

StatefulEvaluator<InputType,OutputType,StateType extends CloneableSerializable> motionModel
Model that determines how inputs and the previous state are updated.


observationModel

Evaluator<InputType,OutputType> observationModel
Model that determines how the state is observed.

Class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression extends DefaultKernelContainer<InputType> implements Serializable

Serialized Fields

outputVariance

double outputVariance
Assumed known variance of the outputs (measurements), must be greater than or equal to zero.

Class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression.PredictiveDistribution extends AbstractCloneableSerializable implements Serializable

Serialized Fields

inputs

ArrayList<E> inputs
Inputs that we've condition on.


posterior

MultivariateGaussian posterior
Posterior distribution of the Gaussian process given the data.

Class gov.sandia.cognition.statistics.bayesian.ImportanceSampling extends AbstractRandomized implements Serializable

Serialized Fields

updater

ImportanceSampling.Updater<ObservationType,ParameterType> updater
Updater for the ImportanceSampling algorithm.


numSamples

int numSamples
Number of samples.

Class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater extends AbstractCloneableSerializable implements Serializable

Serialized Fields

conjuctive

BayesianParameter<ParameterType,ConditionalType extends Distribution<?>,PriorType extends Distribution<ParameterType>> conjuctive
Defines the parameter that connects the conditional and prior distributions.

Class gov.sandia.cognition.statistics.bayesian.KalmanFilter extends AbstractKalmanFilter implements Serializable

Serialized Fields

model

LinearDynamicalSystem model
Motion model of the underlying system.

Class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm extends AbstractMarkovChainMonteCarlo<ObservationType,ParameterType> implements Serializable

Serialized Fields

currentLogLikelihood

double currentLogLikelihood
Log Likelihood of the current parameters.


updater

MetropolisHastingsAlgorithm.Updater<ObservationType,ParameterType> updater
The object that makes proposal samples from the current location.

Class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel extends DirichletProcessMixtureModel<ObservationType> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ClusterUpdaterTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

observations

Collection<E> observations
Observations that comprise the cluster


localUpdater

DirichletProcessMixtureModel.Updater<ObservationType> localUpdater
Local clone of the updater, needed to ensure thread safety

Class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ObservationAssignmentTask extends AbstractCloneableSerializable implements Serializable

Serialized Fields

observations

Collection<E> observations
Observations to assign


weights

double[] weights
Weights that are re-used


assignments

ArrayList<E> assignments
Resulting assignments


logConditional

DirichletProcessMixtureModel.DPMMLogConditional logConditional
Log conditional of the previous sample

Class gov.sandia.cognition.statistics.bayesian.RejectionSampling extends AbstractRandomized implements Serializable

Serialized Fields

numSamples

int numSamples
Number of samples.


updater

RejectionSampling.Updater<ObservationType,ParameterType> updater
Updater for the ImportanceSampling algorithm.

Class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater extends AbstractCloneableSerializable implements Serializable

Serialized Fields

conjuctive

BayesianParameter<ParameterType,ConditionalType extends Distribution<?>,PriorType extends Distribution<ParameterType>> conjuctive
Defines the parameter that connects the conditional and prior distributions.


scale

Double scale
Scale factor to multiply the sampler function by to envelop the conjunctive distribution.


sampler

ProbabilityFunction<DataType> sampler
Distribution from which we sample and envelop the conjunctive distribution.


proposals

int proposals
Number of proposals suggested

Class gov.sandia.cognition.statistics.bayesian.SamplingImportanceResamplingParticleFilter extends AbstractParticleFilter<ObservationType,ParameterType> implements Serializable

Serialized Fields

particlePctThreadhold

double particlePctThreadhold
Percentage of effective particles, below which we resample.


Package gov.sandia.cognition.statistics.bayesian.conjugate

Class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator extends AbstractBatchAndIncrementalLearner<ObservationType,BeliefType extends ClosedFormDistribution<ParameterType>> implements Serializable

Serialized Fields

parameter

BayesianParameter<ParameterType,ConditionalType extends Distribution<?>,PriorType extends Distribution<ParameterType>> parameter
Bayesian hyperparameter relationship between the conditional distribution and the conjugate prior distribution.

Class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Number,Double,BernoulliDistribution,BetaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,BernoulliDistribution,BetaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Number,Double,BinomialDistribution,BetaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,BinomialDistribution,BetaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Double,Double,ExponentialDistribution,GammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,ExponentialDistribution,GammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Double,Double,GammaDistribution,GammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,GammaDistribution,GammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Vector,Vector,MultinomialDistribution,DirichletDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator.Parameter extends AbstractBayesianParameter<Vector,MultinomialDistribution,DirichletDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Vector,Vector,MultivariateGaussian,MultivariateGaussian> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator.Parameter extends AbstractBayesianParameter<Vector,MultivariateGaussian,MultivariateGaussian> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Vector,Matrix,MultivariateGaussian,NormalInverseWishartDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter extends AbstractBayesianParameter<Matrix,MultivariateGaussian,NormalInverseWishartDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Number,Double,PoissonDistribution,GammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,PoissonDistribution,GammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Double,Double,UniformDistribution,ParetoDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,UniformDistribution,ParetoDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Double,Double,UnivariateGaussian,UnivariateGaussian> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator.Parameter extends AbstractBayesianParameter<Double,UnivariateGaussian,UnivariateGaussian> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Double,Vector,UnivariateGaussian,NormalInverseGammaDistribution> implements Serializable

Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator.Parameter extends AbstractBayesianParameter<Vector,UnivariateGaussian,NormalInverseGammaDistribution> implements Serializable


Package gov.sandia.cognition.statistics.distribution

Class gov.sandia.cognition.statistics.distribution.BernoulliDistribution extends AbstractClosedFormUnivariateDistribution<Number> implements Serializable

Serialized Fields

p

double p
Bernoulli parameter, where the distribution takes value "1" with probability "p" and value "0" with probability 1-p.

Class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.CDF extends BernoulliDistribution implements Serializable

Class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.PMF extends BernoulliDistribution implements Serializable

Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution extends AbstractClosedFormUnivariateDistribution<Number> implements Serializable

Serialized Fields

n

int n
Number of observations, similar to the Binomial N, must be greater than zero


shape

double shape
Shape, similar to the beta parameter shape, must be greater than zero


scale

double scale
Scale, similar to the beta parameter scale, must be greater than zero

Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.CDF extends BetaBinomialDistribution implements Serializable

Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.MomentMatchingEstimator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.PMF extends BetaBinomialDistribution implements Serializable

Class gov.sandia.cognition.statistics.distribution.BetaDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable

Serialized Fields

alpha

double alpha
Alpha shape parameter, must be greater than 0 (typically greater than 1)


beta

double beta
Alpha shape parameter, must be greater than 0 (typically greater than 1)

Class