gov.sandia.cognition.learning.function.categorization

Class DiagonalConfidenceWeightedBinaryCategorizer

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer<InputType>

gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer<Vectorizable>

gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer

gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer

gov.sandia.cognition.learning.function.categorization.DiagonalConfidenceWeightedBinaryCategorizer

All Implemented Interfaces:

Evaluator<Vectorizable,java.lang.Boolean>, BinaryCategorizer<Vectorizable>, Categorizer<Vectorizable,java.lang.Boolean>, ConfidenceWeightedBinaryCategorizer, DiscriminantBinaryCategorizer<Vectorizable>, DiscriminantCategorizer<Vectorizable,java.lang.Boolean,java.lang.Double>, ThresholdBinaryCategorizer<Vectorizable>, VectorInputEvaluator<Vectorizable,java.lang.Boolean>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

public class DiagonalConfidenceWeightedBinaryCategorizer
extends AbstractConfidenceWeightedBinaryCategorizer

A confidence-weighted linear predictor with a diagonal covariance, which is stored as a vector.

Since:

3.3.0

Author:

Justin Basilico

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected Vector	variance The variance values, which is the diagonal of the covariance matrix.

Fields inherited from class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer

bias, DEFAULT_BIAS, weights

Fields inherited from class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer

BINARY_CATEGORIES

Constructor Summary

Constructors

Constructor and Description
DiagonalConfidenceWeightedBinaryCategorizer() Creates a new DiagonalConfidenceWeightedBinaryCategorizer.

Method Summary

Modifier and Type	Method and Description
UnivariateGaussian	evaluateAsGaussian(Vectorizable input) Returns the univariate Gaussian distribution over the output of the distribution of weight vectors times the input, with the confidence that the categorizer was trained using.
DiagonalMatrix	getCovariance() Gets the covariance matrix of the categorizer.
Vector	getVariance() Gets the variance vector.
boolean	isInitialized() Determines if this category has been initialized with a mean and covariance.
void	setVariance(Vector variance) Sets the variance vector.

Methods inherited from class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer

createWeightDistribution, evaluateAsBernoulli, getMean, setMean

Methods inherited from class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer

clone, evaluateAsDouble, evaluateAsDouble, getBias, getInputDimensionality, getThreshold, getWeights, setBias, setThreshold, setWeights, toString

Methods inherited from class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer

evaluate, evaluateWithDiscriminant

Methods inherited from class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer

getCategories

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.math.matrix.VectorInputEvaluator

getInputDimensionality

Methods inherited from interface gov.sandia.cognition.learning.function.categorization.ThresholdBinaryCategorizer

getThreshold, setThreshold

Methods inherited from interface gov.sandia.cognition.learning.function.categorization.DiscriminantBinaryCategorizer

evaluateAsDouble

Methods inherited from interface gov.sandia.cognition.learning.function.categorization.DiscriminantCategorizer

evaluateWithDiscriminant

Methods inherited from interface gov.sandia.cognition.learning.function.categorization.Categorizer

getCategories

Methods inherited from interface gov.sandia.cognition.evaluator.Evaluator

evaluate

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

clone

Field Detail

variance

protected Vector variance

The variance values, which is the diagonal of the covariance matrix. It is stored as a vector to avoid needing to instantiate and use matrix operations with it.

Constructor Detail

DiagonalConfidenceWeightedBinaryCategorizer

public DiagonalConfidenceWeightedBinaryCategorizer()

Creates a new DiagonalConfidenceWeightedBinaryCategorizer.

Method Detail

evaluateAsGaussian

public UnivariateGaussian evaluateAsGaussian(Vectorizable input)

Description copied from interface: ConfidenceWeightedBinaryCategorizer

Returns the univariate Gaussian distribution over the output of the distribution of weight vectors times the input, with the confidence that the categorizer was trained using.

Parameters:

input - The input to evaluate.

Returns:

The distribution of outputs as a Gaussian.

isInitialized

public boolean isInitialized()

Description copied from interface: ConfidenceWeightedBinaryCategorizer

Determines if this category has been initialized with a mean and covariance.

Specified by:

isInitialized in interface ConfidenceWeightedBinaryCategorizer

Overrides:

isInitialized in class AbstractConfidenceWeightedBinaryCategorizer

Returns:

True if this categorizer has been initialized. Otherwise, false.

getCovariance

public DiagonalMatrix getCovariance()

Description copied from interface: ConfidenceWeightedBinaryCategorizer

Gets the covariance matrix of the categorizer.

Returns:

The covariance matrix.

getVariance

public Vector getVariance()

Gets the variance vector. Used as the diagonal of the covariance matrix.

Returns:

The variance vector.

setVariance

public void setVariance(Vector variance)

Sets the variance vector. Used as the diagonal of the covariance matrix.

Parameters:

variance - The variance vector.