Uses of Interface
gov.sandia.cognition.learning.function.categorization.DiscriminantCategorizer

Packages that use DiscriminantCategorizer

Package	Description
gov.sandia.cognition.learning.algorithm.bayes	Provides algorithms for computing Bayesian categorizers.
gov.sandia.cognition.learning.algorithm.delta	Provides an abstract class for helping to implement variants of the Burrows' Delta algorithm.
gov.sandia.cognition.learning.algorithm.ensemble	Provides ensemble methods.
gov.sandia.cognition.learning.algorithm.perceptron	Provides the Perceptron algorithm and some of its variations.
gov.sandia.cognition.learning.algorithm.perceptron.kernel
gov.sandia.cognition.learning.function.categorization	Provides functions that output a discrete set of categories.

Uses of DiscriminantCategorizer in gov.sandia.cognition.learning.algorithm.bayes

Classes in gov.sandia.cognition.learning.algorithm.bayes that implement DiscriminantCategorizer

Modifier and Type	Class and Description
class	DiscreteNaiveBayesCategorizer<InputType,CategoryType> Implementation of a Naive Bayes Classifier for Discrete Data.
class	VectorNaiveBayesCategorizer<CategoryType,DistributionType extends UnivariateProbabilityDensityFunction> A naive Bayesian categorizer that takes an input vector and applies an independent scalar probability density function to each one.

Uses of DiscriminantCategorizer in gov.sandia.cognition.learning.algorithm.delta

Classes in gov.sandia.cognition.learning.algorithm.delta that implement DiscriminantCategorizer

Modifier and Type	Class and Description
class	AbstractDeltaCategorizer<CategoryType> The Burrows Delta algorithm is primarily used for authorship attribution, but can be used for other applications.
class	BurrowsDeltaCategorizer<CategoryType> The regular Burrows' Delta algorithm implementation.
class	CosineDeltaCategorizer<CategoryType> The Cosine Delta algorithm implementation.

Uses of DiscriminantCategorizer in gov.sandia.cognition.learning.algorithm.ensemble

Classes in gov.sandia.cognition.learning.algorithm.ensemble that implement DiscriminantCategorizer

Modifier and Type	Class and Description
class	VotingCategorizerEnsemble<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>> An ensemble of categorizers that determine the result based on an equal-weight vote.
class	WeightedBinaryEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends java.lang.Boolean>> The WeightedBinaryEnsemble class implements an Ensemble of BinaryCategorizer objects where each categorizer is assigned a weight and the category is selected by choosing the one with the largest sum of weights.
class	WeightedVotingCategorizerEnsemble<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>> An ensemble of categorizers where each ensemble member is evaluated with the given input to find the category to which its weighted votes are assigned.

Uses of DiscriminantCategorizer in gov.sandia.cognition.learning.algorithm.perceptron

Classes in gov.sandia.cognition.learning.algorithm.perceptron that implement DiscriminantCategorizer

Modifier and Type	Class and Description
static class	OnlineShiftingPerceptron.LinearResult This is the result learned by the shifting perceptron.

Uses of DiscriminantCategorizer in gov.sandia.cognition.learning.algorithm.perceptron.kernel

Classes in gov.sandia.cognition.learning.algorithm.perceptron.kernel that implement DiscriminantCategorizer

Modifier and Type	Class and Description
static class	Forgetron.Result<InputType> The result object learned by the Forgetron, which extends the DefaultKernelBinaryCategorizer with some additional state information needed in the update step.

Uses of DiscriminantCategorizer in gov.sandia.cognition.learning.function.categorization

Subinterfaces of DiscriminantCategorizer in gov.sandia.cognition.learning.function.categorization

Modifier and Type	Interface and Description
interface	ConfidenceWeightedBinaryCategorizer Interface for a confidence-weighted binary categorizer, which defines a distribution over linear binary categorizers.
interface	DiscriminantBinaryCategorizer<InputType> Interface for a linear discriminant categorizer in the binary categorization domain.
interface	ThresholdBinaryCategorizer<InputType> Interface for a binary categorizer that uses a threshold to determine the categorization.

Classes in gov.sandia.cognition.learning.function.categorization that implement DiscriminantCategorizer

Modifier and Type	Class and Description
class	AbstractConfidenceWeightedBinaryCategorizer Unit tests for class AbstractConfidenceWeightedBinaryCategorizer.
class	AbstractDiscriminantBinaryCategorizer<InputType> An abstract implementation of the DiscriminantBinaryCategorizer interface.
class	AbstractDiscriminantCategorizer<InputType,CategoryType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> An abstract implementation of the DiscriminantCategorizer interface.
class	AbstractThresholdBinaryCategorizer<InputType> Categorizer that first maps the input space onto a real value, then uses a threshold to map the result onto lowValue (for strictly less than the threshold) or highValue (for greater than or equal to the threshold).
class	BinaryVersusCategorizer<InputType,CategoryType> An adapter that allows binary categorizers to be adapted for multi-category problems by applying a binary categorizer to each pair of categories.
class	DefaultConfidenceWeightedBinaryCategorizer A default implementation of the ConfidenceWeightedBinaryCategorizer that stores a full mean and covariance matrix.
class	DefaultKernelBinaryCategorizer<InputType> A default implementation of the KernelBinaryCategorizer that uses the standard way of representing the examples (supports) using a DefaultWeightedValue.
class	DiagonalConfidenceWeightedBinaryCategorizer A confidence-weighted linear predictor with a diagonal covariance, which is stored as a vector.
class	FisherLinearDiscriminantBinaryCategorizer A Fisher Linear Discriminant classifier, which creates an optimal linear separating plane between two Gaussian classes of different covariances.
class	KernelBinaryCategorizer<InputType,EntryType extends WeightedValue<? extends InputType>> The KernelBinaryCategorizer class implements a binary categorizer that uses a kernel to do its categorization.
class	LinearBinaryCategorizer The LinearBinaryCategorizer class implements a binary categorizer that is implemented by a linear function.
class	LinearMultiCategorizer<CategoryType> A multi-category version of the LinearBinaryCategorizer that keeps a separate LinearBinaryCategorizer for each category.
class	MaximumAPosterioriCategorizer<ObservationType,CategoryType> Categorizer that returns the category with the highest posterior likelihood for a given observation.
class	ScalarFunctionToBinaryCategorizerAdapter<InputType> Adapts a scalar function to be a categorizer using a threshold.
class	ScalarThresholdBinaryCategorizer The ScalarThresholdBinaryCategorizer class implements a binary categorizer that uses a threshold to categorize a given double.
class	VectorElementThresholdCategorizer The VectorElementThresholdCategorizer class implements a BinaryCategorizer that categorizes an input vector by applying a threshold to an element in a the vector.
class	WinnerTakeAllCategorizer<InputType,CategoryType> Adapts an evaluator that outputs a vector to be used as a categorizer.