svm5
代码说明：
说明： 支持向量机回归(SVR)理论是建立在支持向量机分类问题的基础上的，确Vapnik通过引入不敏感损失函数 ，将SVM分类理论中得到的结果推广，使其可以用于函数回归。(The theory of support vector machine regression (SVR) is based on the classification of support vector machines. Vapnik extends the results of SVM classification theory by introducing insensitive loss function, so that it can be used in functional regression.)
文件列表：
Contents.m, 2905 , 2002-02-25
LinearSVC.m, 1978 , 2002-02-15
Normalize.m, 234 , 2001-12-06
cmap.mat, 1728 , 1997-08-13
demos.m, 587 , 2002-01-03
mexSVMClass.dll, 61440 , 2002-04-12
mexSVMClass.m, 5181 , 2002-02-15
mexSVMClass.mexglx, 166002 , 2002-04-12
mexSVMClass.mexhp7, 127289 , 2002-03-21
mexSVMClass.mexsol, 232932 , 2002-03-21
mexSVMTrain.dll, 73728 , 2002-04-12
mexSVMTrain.m, 4332 , 2002-02-15
mexSVMTrain.mexglx, 165010 , 2002-04-12
mexSVMTrain.mexhp7, 127290 , 2002-03-21
mexSVMTrain.mexsol, 231836 , 2002-03-21
one_RbfSVC.m, 2557 , 2002-02-25
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