gov.sandia.cognition.learning.algorithm

Class AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>

gov.sandia.cognition.learning.algorithm.AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType>

Type Parameters:

InputType - The type of input data in the input-output pair that the learner can learn from. The Evaluator learned from the algorithm also takes this as the input parameter.

OutputType - The type of output data in the input-output pair that the learner can learn from. The Evaluator learned from the algorithm also produces this as its output.

ResultType - The type of object created by the learning algorithm. For example, a LinearBinaryCategorizer.

All Implemented Interfaces:

BatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,ResultType>, IncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>, SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType>, SupervisedBatchLearner<InputType,OutputType,ResultType>, SupervisedIncrementalLearner<InputType,OutputType,ResultType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

AbstractOnlineKernelBinaryCategorizerLearner, AbstractOnlineLinearBinaryCategorizerLearner, AdaptiveRegularizationOfWeights, ConfidenceWeightedDiagonalDeviation, ConfidenceWeightedDiagonalVariance, OnlineBaggingCategorizerLearner, OnlineVotedPerceptron

public abstract class AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>>
extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>
implements SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType>

An abstract implementation of the batch and incremental learning for an incremental supervised learner.

Since:

3.2.0

Author:

Justin Basilico

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractSupervisedBatchAndIncrementalLearner() Creates a new AbstractSupervisedBatchAndIncrementalLearner.

Method Summary

Modifier and Type	Method and Description
void	update(ResultType target, InputOutputPair<? extends InputType,OutputType> data) The update method updates an object of ResultType using the given new data of type DataType, using some form of "learning" algorithm.

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

clone, learn, learn, update

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.SupervisedIncrementalLearner

update

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

learn

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

learn

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

createInitialLearnedObject, update

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

clone

Constructor Detail

AbstractSupervisedBatchAndIncrementalLearner

public AbstractSupervisedBatchAndIncrementalLearner()

Creates a new AbstractSupervisedBatchAndIncrementalLearner.

Method Detail

update

public void update(ResultType target,
                   InputOutputPair<? extends InputType,OutputType> data)

Description copied from interface: IncrementalLearner

The update method updates an object of ResultType using the given new data of type DataType, using some form of "learning" algorithm.

Specified by:

update in interface IncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType extends Evaluator<? super InputType,? extends OutputType>>

Parameters:

target - The object to update.

data - The new data for the learning algorithm to use to update the object.