gov.sandia.cognition.learning.algorithm.ensemble
Class CategoryBalancedBaggingLearner<InputType,CategoryType>

java.lang.Object
  gov.sandia.cognition.util.AbstractCloneableSerializable
      gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
          gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm<ResultType>
              gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner<Collection<? extends InputOutputPair<? extends InputType,OutputType>>,ResultType>
                  gov.sandia.cognition.learning.algorithm.AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,EnsembleType>
                      gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>
                          gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner<InputType,CategoryType>
                              gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner<InputType,CategoryType>

Type Parameters:

InputType - The input type for supervised learning. Passed on to the internal learning algorithm. Also the input type for the learned ensemble.

CategoryType - The output type for supervised learning. Passed on to the internal learning algorithm. Also the output type of the learned ensemble.

All Implemented Interfaces:

AnytimeAlgorithm<WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>, IterativeAlgorithm, StoppableAlgorithm, AnytimeBatchLearner<Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>, BatchLearner<Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>, BatchLearnerContainer<BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>>>, SupervisedBatchLearner<InputType,CategoryType,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>, CloneableSerializable, Randomized, Serializable, Cloneable

public class CategoryBalancedBaggingLearner<InputType,CategoryType>
extends BaggingCategorizerLearner<InputType,CategoryType>

An extension of the basic bagging learner that attempts to sample bags that have equal numbers of examples from every category.

Since:

3.3.0

Author:

Justin Basilico

See Also:

Serialized Form

Field Summary

protected ArrayList<CategoryType>	categoryList The list of categories.
protected HashMap<CategoryType,ArrayList<Integer>>	dataPerCategory The mapping of categories to indices of examples belonging to the category.

Fields inherited from class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner

bag, dataInBag, dataList, DEFAULT_MAX_ITERATIONS, DEFAULT_PERCENT_TO_SAMPLE, ensemble, learner, percentToSample, random

Fields inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

data, keepGoing

Fields inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

maxIterations

Fields inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

DEFAULT_ITERATION, iteration

Constructor Summary

CategoryBalancedBaggingLearner()
Creates a new instance of CategoryBalancedBaggingLearner.

CategoryBalancedBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>> learner)
Creates a new instance of CategoryBalancedBaggingLearner.

CategoryBalancedBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>> learner, int maxIterations, double percentToSample, Random random)
Creates a new instance of CategoryBalancedBaggingLearner.

Method Summary

protected void	cleanupAlgorithm() Called to clean up the learning algorithm's state after learning has finished.
protected void	fillBag(int sampleCount) Fills the internal bag field by sampling the given number of samples.
protected boolean	initializeAlgorithm() Called to initialize the learning algorithm's state based on the data that is stored in the data field.

Methods inherited from class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner

addEnsembleMember, createInitialEnsemble

Methods inherited from class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner

getBag, getDataInBag, getDataList, getEnsemble, getLearner, getPercentToSample, getRandom, getResult, setBag, setDataInBag, setDataList, setEnsemble, setLearner, setPercentToSample, setRandom, step

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

clone, getData, getKeepGoing, learn, setData, setKeepGoing, stop

Methods inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

getMaxIterations, isResultValid, setMaxIterations

Methods inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

addIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, getIteration, getListeners, removeIterativeAlgorithmListener, setIteration, setListeners

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner

learn

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Methods inherited from interface gov.sandia.cognition.algorithm.AnytimeAlgorithm

getMaxIterations, setMaxIterations

Methods inherited from interface gov.sandia.cognition.algorithm.IterativeAlgorithm

addIterativeAlgorithmListener, getIteration, removeIterativeAlgorithmListener

Methods inherited from interface gov.sandia.cognition.algorithm.StoppableAlgorithm

isResultValid

Field Detail

categoryList

protected ArrayList<CategoryType> categoryList

The list of categories.

dataPerCategory

protected HashMap<CategoryType,ArrayList<Integer>> dataPerCategory

The mapping of categories to indices of examples belonging to the category.

Constructor Detail

CategoryBalancedBaggingLearner

public CategoryBalancedBaggingLearner()

Creates a new instance of CategoryBalancedBaggingLearner.

CategoryBalancedBaggingLearner

public CategoryBalancedBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>> learner)

Creates a new instance of CategoryBalancedBaggingLearner.

Parameters:

learner - The learner to use to create the categorizer on each iteration.

CategoryBalancedBaggingLearner

public CategoryBalancedBaggingLearner(BatchLearner<? super Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>> learner,
                                      int maxIterations,
                                      double percentToSample,
                                      Random random)

Creates a new instance of CategoryBalancedBaggingLearner.

Parameters:

learner - The learner to use to create the categorizer on each iteration.

maxIterations - The maximum number of iterations to run for, which is also the number of learners to create.

percentToSample - The percentage of the total size of the data to sample on each iteration. Must be positive.

random - The random number generator to use.

Method Detail

initializeAlgorithm

protected boolean initializeAlgorithm()

Description copied from class: AbstractAnytimeBatchLearner

Called to initialize the learning algorithm's state based on the data that is stored in the data field. The return value indicates if the algorithm can be run or not based on the initialization.

Overrides:

initializeAlgorithm in class AbstractBaggingLearner<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>

Returns:

True if the learning algorithm can be run and false if it cannot.

fillBag

protected void fillBag(int sampleCount)

Description copied from class: AbstractBaggingLearner

Fills the internal bag field by sampling the given number of samples.

Overrides:

fillBag in class AbstractBaggingLearner<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>

Parameters:

sampleCount - The number to sample.

cleanupAlgorithm

protected void cleanupAlgorithm()

Description copied from class: AbstractAnytimeBatchLearner

Called to clean up the learning algorithm's state after learning has finished.

Overrides:

cleanupAlgorithm in class AbstractBaggingLearner<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>>