SVM core idea is: For the non-linear input space can be divided into the case, select an appropriate nonlinear mapping the input space sample point is mapped to a high-dimensional space, then through a series of nuclear function, the parameter factor choose the optimal point interface.

SVM\COPYRIGHT
...\DATA.mat
...\heart_scale.mat
...\hs_err_pid2156.log
...\hs_err_pid2576.log
...\hs_err_pid3412.log
...\libsvmread.c
...\libsvmread.mexw32
...\libsvmwrite.c
...\libsvmwrite.mexw32
...\LogisticR.m
...\make.m
...\Makefile
...\README
...\sll_opts.m
...\svm.cpp
...\svm.h
...\svmpredict.c
...\svmpredict.mexw32
...\svmtrain.c
...\svmtrain.mexw32
...\svm_model_matlab.c
...\svm_model_matlab.h
...\Task1.asv
...\Task1.m
...\Task2.m
SVM

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