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

Packages that use Categorizer

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.algorithm.tree	Provides decision tree learning algorithms.
gov.sandia.cognition.learning.function.categorization	Provides functions that output a discrete set of categories.

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

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

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 Categorizer in gov.sandia.cognition.learning.algorithm.delta

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

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 Categorizer in gov.sandia.cognition.learning.algorithm.ensemble

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

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 Categorizer in gov.sandia.cognition.learning.algorithm.perceptron

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

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

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

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

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 Categorizer in gov.sandia.cognition.learning.algorithm.tree

Classes in gov.sandia.cognition.learning.algorithm.tree with type parameters of type Categorizer

Modifier and Type	Interface and Description
interface	DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>> The DeciderLearner interface defines the functionality of a learner that can be used to learn a decision function inside a decision tree.

Classes in gov.sandia.cognition.learning.algorithm.tree that implement Categorizer

Modifier and Type	Class and Description
class	CategorizationTree<InputType,OutputType> The CategorizationTree class extends the DecisionTree class to implement a decision tree that does categorization.

Fields in gov.sandia.cognition.learning.algorithm.tree declared as Categorizer

Modifier and Type	Field and Description
protected Categorizer<? super InputType,? extends InteriorType>	AbstractDecisionTreeNode.decider The decider used to make a decision as to which child use.

Methods in gov.sandia.cognition.learning.algorithm.tree that return Categorizer

Modifier and Type	Method and Description
Categorizer<? super InputType,? extends InteriorType>	AbstractDecisionTreeNode.getDecider() Gets the decider used at this node.

Methods in gov.sandia.cognition.learning.algorithm.tree with parameters of type Categorizer

Modifier and Type	Method and Description
protected <DecisionType> void	AbstractDecisionTreeLearner.learnChildNodes(AbstractDecisionTreeNode<InputType,OutputType,DecisionType> node, java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data, Categorizer<? super InputType,? extends DecisionType> decider) Learns the child nodes for a node using the given data at the node plus the decision function for the node.
void	AbstractDecisionTreeNode.setDecider(Categorizer<? super InputType,? extends InteriorType> decider) Sets the decider used at this node.
<DecisionType> java.util.Map<DecisionType,java.util.LinkedList<InputOutputPair<? extends InputType,OutputType>>>	AbstractDecisionTreeLearner.splitData(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data, Categorizer<? super InputType,? extends DecisionType> decider) Splits the data into new lists based on the given decision function.

Constructors in gov.sandia.cognition.learning.algorithm.tree with parameters of type Categorizer

Constructor and Description
AbstractDecisionTreeNode(DecisionTreeNode<InputType,OutputType> parent, Categorizer<? super InputType,? extends InteriorType> decider, java.lang.Object incomingValue) Creates a new instance of CategorizationTreeNode.
CategorizationTreeNode(DecisionTreeNode<InputType,OutputType> parent, Categorizer<? super InputType,? extends InteriorType> decider, OutputType outputCategory, java.lang.Object incomingValue) Creates a new instance of CategorizationTreeNode.
RegressionTreeNode(DecisionTreeNode<InputType,java.lang.Double> parent, Categorizer<? super InputType,? extends InteriorType> decider, double value) Creates a new instance of RegressionTreeNode.
RegressionTreeNode(DecisionTreeNode<InputType,java.lang.Double> parent, Categorizer<? super InputType,? extends InteriorType> decider, Evaluator<? super InputType,java.lang.Double> scalarFunction, double value, java.lang.Object incomingValue) Creates a new instance of RegressionTreeNode.

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

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

Modifier and Type	Interface and Description
interface	BinaryCategorizer<InputType> The BinaryCategorizer extends the Categorizer interface by enforcing that the output categories are boolean values, which means that the categorizer is performing binary categorization.
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	DiscriminantCategorizer<InputType,CategoryType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> Interface for a Categorizer that can produce a value to discriminate between how well different instances fit a given category.
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 Categorizer

Modifier and Type	Class and Description
class	AbstractBinaryCategorizer<InputType> The AbstractBinaryCategorizer implements the commonality of the BinaryCategorizer, holding the collection of possible values.
class	AbstractCategorizer<InputType,CategoryType> An abstract implementation of the Categorizer interface.
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	CompositeCategorizer<InputType,IntermediateType,CategoryType> Composes a preprocessor function with a categorizer.
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	EvaluatorToCategorizerAdapter<InputType,CategoryType> The EvaluatorToCategorizerAdapter class implements an adapter from a general Evaluator to be a Categorizer.
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.

Fields in gov.sandia.cognition.learning.function.categorization declared as Categorizer

Modifier and Type	Field and Description
protected Categorizer<? super IntermediateType,? extends CategoryType>	CompositeCategorizer.categorizer The categorizer.

Methods in gov.sandia.cognition.learning.function.categorization that return Categorizer

Modifier and Type	Method and Description
Categorizer<? super IntermediateType,? extends CategoryType>	CompositeCategorizer.getCategorizer() Gets the categorizer, which takes the output of the preprocessor and categorizes it.

Methods in gov.sandia.cognition.learning.function.categorization with parameters of type Categorizer

Modifier and Type	Method and Description
void	CompositeCategorizer.setCategorizer(Categorizer<? super IntermediateType,? extends CategoryType> categorizer) Sets the categorizer, which takes the output of the preprocessor and categorizes it.

Constructors in gov.sandia.cognition.learning.function.categorization with parameters of type Categorizer

Constructor and Description
CompositeCategorizer(Evaluator<? super InputType,? extends IntermediateType> preprocessor, Categorizer<? super IntermediateType,? extends CategoryType> categorizer) Creates a new CompositeCategorizer.