gov.sandia.cognition.learning.function.scalar
Class VectorFunctionToScalarFunction.Learner<InputType>

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction.Learner<InputType>
Type Parameters:
InputType - The input type for supervised learning.
All Implemented Interfaces:
BatchLearner<Collection<? extends InputOutputPair<? extends InputType,Double>>,VectorFunctionToScalarFunction<InputType>>, SupervisedBatchLearner<InputType,Double,VectorFunctionToScalarFunction<InputType>>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
VectorFunctionToScalarFunction<InputType>

public static class VectorFunctionToScalarFunction.Learner<InputType>
extends AbstractCloneableSerializable
implements SupervisedBatchLearner<InputType,Double,VectorFunctionToScalarFunction<InputType>>

The VectorFunctionToScalarFunction.Learner class implements a simple learner for a VectorFunctionToScalarFunction that allows a learning algorithm that outputs a vector function to be adapted to learn on data whose output are doubles.

See Also:
Serialized Form

Field Summary
protected  BatchLearner<Collection<? extends InputOutputPair<? extends InputType,Vector>>,? extends Evaluator<? super InputType,? extends Vectorizable>> vectorLearner
          The supervised learner that learns on vectors as outputs.
 
Constructor Summary
VectorFunctionToScalarFunction.Learner()
          Creates a new VectorFunctionToScalarFunction.Learner.
VectorFunctionToScalarFunction.Learner(BatchLearner<Collection<? extends InputOutputPair<? extends InputType,Vector>>,? extends Evaluator<? super InputType,? extends Vectorizable>> vectorLearner)
          Creates a new VectorFunctionToScalarFunction.Learner.
 
Method Summary
 VectorFunctionToScalarFunction.Learner<InputType> clone()
          This makes public the clone method on the Object class and removes the exception that it throws.
 VectorFunctionToScalarFunction<InputType> learn(Collection<? extends InputOutputPair<? extends InputType,Double>> data)
          The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

vectorLearner

protected BatchLearner<Collection<? extends InputOutputPair<? extends InputType,Vector>>,? extends Evaluator<? super InputType,? extends Vectorizable>> vectorLearner
The supervised learner that learns on vectors as outputs.

Constructor Detail

VectorFunctionToScalarFunction.Learner

public VectorFunctionToScalarFunction.Learner()
Creates a new VectorFunctionToScalarFunction.Learner.


VectorFunctionToScalarFunction.Learner

public VectorFunctionToScalarFunction.Learner(BatchLearner<Collection<? extends InputOutputPair<? extends InputType,Vector>>,? extends Evaluator<? super InputType,? extends Vectorizable>> vectorLearner)
Creates a new VectorFunctionToScalarFunction.Learner.

Parameters:
vectorLearner - The supervised learner to use that learns on vectors as outputs.
Method Detail

clone

public VectorFunctionToScalarFunction.Learner<InputType> clone()
Description copied from class: AbstractCloneableSerializable
This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:
clone in interface CloneableSerializable
Overrides:
clone in class AbstractCloneableSerializable
Returns:
A clone of this object.

learn

public VectorFunctionToScalarFunction<InputType> learn(Collection<? extends InputOutputPair<? extends InputType,Double>> data)
Description copied from interface: BatchLearner
The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.

Specified by:
learn in interface BatchLearner<Collection<? extends InputOutputPair<? extends InputType,Double>>,VectorFunctionToScalarFunction<InputType>>
Parameters:
data - The data that the learning algorithm will use to create an object of ResultType.
Returns:
The object that is created based on the given data using the learning algorithm.