gov.sandia.cognition.learning.algorithm.confidence

Class ConfidenceWeightedDiagonalVarianceProject

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.ConfidenceWeightedDiagonalVariance

gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVarianceProject

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(title="Confidence-Weighted Linear Classification",
                      author={"Mark Dredze","Koby Crammer","Fernando Pereira"},
                      year=2008,
                      type=Conference,
                      publication="International Conference on Machine Learning",
                      url="http://portal.acm.org/citation.cfm?id=1390190")
public class ConfidenceWeightedDiagonalVarianceProject
extends ConfidenceWeightedDiagonalVariance

An implementation of the Variance algorithm for learning a confidence-weighted linear categorizer. It updates only the diagonal of the covariance matrix, thus computing the variance of each dimension. It is roughly based on the Passive-Aggressive algorithm PA-I, which uses a linear soft margin. This corresponds to the "Variance-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.ConfidenceWeightedDiagonalVariance

confidence, DEFAULT_CONFIDENCE, DEFAULT_DEFAULT_VARIANCE, defaultVariance, phi

Constructor Summary

Constructors

Constructor and Description
ConfidenceWeightedDiagonalVarianceProject() Creates a new ConfidenceWeightedDiagonalVarianceProject with default parameters.
ConfidenceWeightedDiagonalVarianceProject(double confidence, double defaultVariance) Creates a new ConfidenceWeightedDiagonalVarianceProject 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.ConfidenceWeightedDiagonalVariance

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

ConfidenceWeightedDiagonalVarianceProject

public ConfidenceWeightedDiagonalVarianceProject()

Creates a new ConfidenceWeightedDiagonalVarianceProject with default parameters.

ConfidenceWeightedDiagonalVarianceProject

public ConfidenceWeightedDiagonalVarianceProject(double confidence,
                                                 double defaultVariance)

Creates a new ConfidenceWeightedDiagonalVarianceProject 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: ConfidenceWeightedDiagonalVariance

Updates the target using the given input and associated label.

Overrides:

update in class ConfidenceWeightedDiagonalVariance

Parameters:

target - The target to update.

input - The supervised input value.

label - The output label associated with the input.