Uses of Class

Packages that use AbstractBinaryCategorizer
gov.sandia.cognition.learning.algorithm.ensemble Provides ensmble methods. 
gov.sandia.cognition.learning.algorithm.perceptron Provides the Perceptron algorithm and some of its variations. 
gov.sandia.cognition.learning.function.categorization Provides functions that output a discrete set of categories. 

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

Subclasses of AbstractBinaryCategorizer in gov.sandia.cognition.learning.algorithm.ensemble
 class WeightedBinaryEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends 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.

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

Subclasses of AbstractBinaryCategorizer in gov.sandia.cognition.learning.algorithm.perceptron
static class OnlineShiftingPerceptron.LinearResult
          This is the result learned by the shifting perceptron.

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

Subclasses of AbstractBinaryCategorizer in gov.sandia.cognition.learning.algorithm.perceptron.kernel
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 AbstractBinaryCategorizer in gov.sandia.cognition.learning.function.categorization

Subclasses of AbstractBinaryCategorizer in gov.sandia.cognition.learning.function.categorization
 class AbstractConfidenceWeightedBinaryCategorizer
          Unit tests for class AbstractConfidenceWeightedBinaryCategorizer.
 class AbstractDiscriminantBinaryCategorizer<InputType>
          An abstract implementation of the DiscriminantBinaryCategorizer 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 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.