Package gov.sandia.cognition.learning.algorithm.perceptron

Provides the Perceptron algorithm and some of its variations.

See:
          Description

Interface Summary
KernelizableBinaryCategorizerOnlineLearner Interface for an online learner of a linear binary categorizer that can also be used with a kernel function.
LinearizableBinaryCategorizerOnlineLearner<InputType> Interface for an online learner of a kernel binary categorizer that can also be used for learning a linear categorizer.
 

Class Summary
AbstractKernelizableBinaryCategorizerOnlineLearner An abstract implementation of the KernelizableBinaryCategorizerOnlineLearner interface.
AbstractLinearCombinationOnlineLearner An abstract class for online learning of linear binary categorizers that take the form of a weighted sum of inputs.
AbstractOnlineLinearBinaryCategorizerLearner An abstract class for online (incremental) learning algorithms that produce an LinearBinaryCategorizer.
AggressiveRelaxedOnlineMaximumMarginAlgorithm An implementation of the Aggressive Relaxed Online Maximum Margin Algorithm (AROMMA).
Ballseptron An implementation of the Ballseptron algorithm.
BatchMultiPerceptron<CategoryType> Implements a multi-class version of the standard batch Perceptron learning algorithm.
OnlineBinaryMarginInfusedRelaxedAlgorithm An implementation of the binary MIRA algorithm.
OnlineMultiPerceptron<CategoryType> An online, multiple category version of the Perceptron algorithm.
OnlineMultiPerceptron.ProportionalUpdate<CategoryType> Variant of a multi-category Perceptron that performs a proportional weight update on all categories that are scored higher than the true category such that the weights sum to 1.0 and are proportional how much larger the score was for each incorrect category than the true category.
OnlineMultiPerceptron.UniformUpdate<CategoryType> Variant of a multi-category Perceptron that performs a uniform weight update on all categories that are scored higher than the true category such that the weights are equal and sum to -1.
OnlinePassiveAggressivePerceptron An implementation of the Passive-Aggressive algorithm for learning a linear binary categorizer.
OnlinePassiveAggressivePerceptron.AbstractSoftMargin An abstract class for soft-margin versions of the Passive-Aggressive algorithm.
OnlinePassiveAggressivePerceptron.LinearSoftMargin An implementation of the linear soft-margin variant of the Passive- Aggressive algorithm (PA-I).
OnlinePassiveAggressivePerceptron.QuadraticSoftMargin An implementation of the quadratic soft-margin variant of the Passive- Aggressive algorithm (PA-II).
OnlinePerceptron An online version of the classic Perceptron algorithm.
OnlineRampPassiveAggressivePerceptron An implementation of the Ramp Loss Passive Aggressive Perceptron (PA^R) from the referenced paper.
OnlineShiftingPerceptron An implementation of the Shifting Perceptron algorithm.
OnlineShiftingPerceptron.LinearResult This is the result learned by the shifting perceptron.
OnlineVotedPerceptron An online version of the Voted-Perceptron algorithm.
Perceptron The Perceptron class implements the standard Perceptron learning algorithm that learns a binary classifier based on vector input.
RelaxedOnlineMaximumMarginAlgorithm An implementation of the Relaxed Online Maximum Margin Algorithm (ROMMA).
Winnow An implementation of the Winnow incremental learning algorithm.
 

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

Provides the Perceptron algorithm and some of its variations.

Since:
2.0
Author:
Justin Basilico