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% Data sets used by the STPRtool.
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% andersons_task - (dir) Input for demo on Generalized Anderson's task.
% binary_separable - (dir) Input for demo on Linear classification.
% gmm_sample - (
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% Quadratic discriminant function and data mapping.
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% lin2quad - Merges linear rule and quadratic mapping.
% qmap - Quadratic data mapping.
% quadclass - Quadratic classifier.
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% About: St
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% Visualization for pattern recognition.
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% pandr - Visualizes solution of the Generalized Anderson's task.
% pboundary - Plots decision boundary of given classifier in 2D.
% pgauss
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% Support Vector Machines.
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% bsvm2 - Solver for multi-class BSVM with L2-soft margin.
% evalsvm - Trains and evaluates Support Vector Machines classifier.
% mvsvmclass - Majority votin
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% Support Vector Machines.
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% bsvm2 - Multi-class BSVM with L2-soft margin.
% evalsvm - Trains and evaluates Support Vector Machines classifier.
% mvsvmclass - Majority voting multi-cla
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% Miscellaneous functions for STPRtoolbox.
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% adaboost - AdaBoost algorithm.
% adaclass - AdaBoost classifier.
% cerror - Computes classification error.
% crossval - Partions data
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% Kernel machines.
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% extraction - (dir) Kernel feature extraction.
% preimage - (dir) Pre-image problem for RBF kernel.
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% diagker - Returns diagonal of kernel matrix.
% dualcov - Dual
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% Pre-image problem for RBF kernel.
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% rbfpreimg - Schoelkopf's fixed-point algorithm.
% rbfpreimg2 - Gradient optimization.
% rbfpreimg3 - Kwok-Tsang's algorithm.
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% About: Statistical Pattern
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% Kernel feature extraction.
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% gda - Generalized Discriminant Analysis.
% greedyappx - Kernel greedy data approximation.
% greedykpca - Greedy kernel PCA.
% kpca - Kernel Principal