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

Packages that use ThresholdBinaryCategorizer

Package	Description
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 ThresholdBinaryCategorizer in gov.sandia.cognition.learning.algorithm.perceptron

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

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

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

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

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 ThresholdBinaryCategorizer in gov.sandia.cognition.learning.function.categorization

Subinterfaces of ThresholdBinaryCategorizer 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.

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

Modifier and Type	Class and Description
class	AbstractConfidenceWeightedBinaryCategorizer Unit tests for class AbstractConfidenceWeightedBinaryCategorizer.
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	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	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.