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% Quadratic discriminant function and data mapping. % % lin2quad - Merges linear rule and quadratic mapping. % qmap - Quadratic data mapping. % quadclass - Quadratic classifier. % % About: St
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% Visualization for pattern recognition. % % 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. % % 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. % % 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. % % adaboost - AdaBoost algorithm. % adaclass - AdaBoost classifier. % cerror - Computes classification error. % crossval - Partions data
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% Kernel machines. % % extraction - (dir) Kernel feature extraction. % preimage - (dir) Pre-image problem for RBF kernel. % % diagker - Returns diagonal of kernel matrix. % dualcov - Dual
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% Pre-image problem for RBF kernel. % % rbfpreimg - Schoelkopf's fixed-point algorithm. % rbfpreimg2 - Gradient optimization. % rbfpreimg3 - Kwok-Tsang's algorithm. % % About: Statistical Pattern
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% Kernel feature extraction. % % gda - Generalized Discriminant Analysis. % greedyappx - Kernel greedy data approximation. % greedykpca - Greedy kernel PCA. % kpca - Kernel Principal
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% Kernel machines. % % extraction - (dir) Kernel feature extraction. % preimage - (dir) Pre-image problem for RBF kernel. % % diagker - Returns diagonal of kernel matrix. % dualcov - Dual
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% Image denoising using kernel PCA. % % make_noisy_data - Adds Gaussian noise to USPS database. % show_denois_tuning - Plots curves of tuning stage of Kernel PCA. % show_denoising - Image d
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