gov.sandia.cognition.learning.algorithm.confidence

Class ConfidenceWeightedDiagonalDeviationProject

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<Vectorizable,java.lang.Boolean,DiagonalConfidenceWeightedBinaryCategorizer>

gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation

gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviationProject

All Implemented Interfaces:

BatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,java.lang.Boolean>,DiagonalConfidenceWeightedBinaryCategorizer>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends Vectorizable,java.lang.Boolean>>,DiagonalConfidenceWeightedBinaryCategorizer>, IncrementalLearner<InputOutputPair<? extends Vectorizable,java.lang.Boolean>,DiagonalConfidenceWeightedBinaryCategorizer>, SupervisedBatchAndIncrementalLearner<Vectorizable,java.lang.Boolean,DiagonalConfidenceWeightedBinaryCategorizer>, SupervisedBatchLearner<Vectorizable,java.lang.Boolean,DiagonalConfidenceWeightedBinaryCategorizer>, SupervisedIncrementalLearner<Vectorizable,java.lang.Boolean,DiagonalConfidenceWeightedBinaryCategorizer>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

@PublicationReference(author={"Koby Crammer","Mark Dredze","Fernando Pereira"},
                      title="Exact Convex Confidence-Weighted Learning",
                      year=2008,
                      type=Conference,
                      publication="Advances in Neural Information Processing Systems",
                      url="http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.169.3364")
public class ConfidenceWeightedDiagonalDeviationProject
extends ConfidenceWeightedDiagonalDeviation

An implementation of the Standard Deviation (Stdev) algorithm for learning a confidence-weighted categorizer. It updates only the diagonal of the covariance matrix, thus computing the variance for each dimension. This corresponds to the "Stdev-project" version.

Since:

3.3.0

Author:

Justin Basilico

See Also:

Serialized Form

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation

confidence, DEFAULT_CONFIDENCE, DEFAULT_DEFAULT_VARIANCE, defaultVariance, epsilon, phi, psi

Constructor Summary

Constructors

Constructor and Description
ConfidenceWeightedDiagonalDeviationProject() Creates a new ConfidenceWeightedDiagonalDeviationProject with default parameters.
ConfidenceWeightedDiagonalDeviationProject(double confidence, double defaultVariance) Creates a new ConfidenceWeightedDiagonalDeviationProject with the given parameters.

Method Summary

Modifier and Type	Method and Description
void	update(DiagonalConfidenceWeightedBinaryCategorizer target, Vector input, boolean label) Updates the target using the given input and associated label.

Methods inherited from class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation

createInitialLearnedObject, getConfidence, getDefaultVariance, setConfidence, setDefaultVariance, update

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

update

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.BatchAndIncrementalLearner

learn

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

learn

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

update

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

clone

Constructor Detail

ConfidenceWeightedDiagonalDeviationProject

public ConfidenceWeightedDiagonalDeviationProject()

Creates a new ConfidenceWeightedDiagonalDeviationProject with default parameters.

ConfidenceWeightedDiagonalDeviationProject

public ConfidenceWeightedDiagonalDeviationProject(double confidence,
                                                  double defaultVariance)

Creates a new ConfidenceWeightedDiagonalDeviationProject with the given parameters.

Parameters:

confidence - The confidence to use. Must be in [0, 1].

defaultVariance - The default value to initialize the covariance matrix to.

Method Detail

update

public void update(DiagonalConfidenceWeightedBinaryCategorizer target,
                   Vector input,
                   boolean label)

Description copied from class: ConfidenceWeightedDiagonalDeviation

Updates the target using the given input and associated label.

Overrides:

update in class ConfidenceWeightedDiagonalDeviation

Parameters:

target - The target to update.

input - The supervised input value.

label - The output label associated with the input.