Package jsat.classifiers.svm

Class Summary

Class	Description
DCD	Implements Dual Coordinate Descent (DCD) training algorithms for a Linear L1 or L2 Support Vector Machine for binary classification and regression.
DCDs	Implements Dual Coordinate Descent with shrinking (DCDs) training algorithms for a Linear L1 or L2 Support Vector Machine for binary classification and regression.
DCSVM	This is an implementation of the Divide-and-Conquer Support Vector Machine (DC-SVM).
LSSVM	The Least Squares Support Vector Machine (LS-SVM) is an alternative to the standard SVM classifier for regression and binary classification problems.
Pegasos	Implements the linear kernel mini-batch version of the Pegasos SVM classifier.
PegasosK	Implements the kernelized version of the Pegasos algorithm for SVMs.
PlattSMO	An implementation of SVMs using Platt's Sequential Minimum Optimization (SMO) for both Classification and Regression problems.
SBP	Implementation of the Stochastic Batch Perceptron (SBP) algorithm.
SupportVectorLearner	Base class for support vector style learners.
SVMnoBias	This class implements a version of the Support Vector Machine without a bias term.

Enum Summary

Enum	Description
SupportVectorLearner.CacheMode	Determines how the final kernel values are cached.