文件名称:zhichixiangliangjisuanfa(svm)
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SVM支持向量机分类训练算法的matlab实现,对正负样本的分类效果很好.-SVM support vector machine classification training algorithm matlab implementation, the positive and negative samples of the classification effect is very good..
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下载文件列表
zhichixiangliangjisuanfa(svm)\zhichixiangliangjisuanfa(svm)\binomial.m
.............................\.............................\centrefig.m
.............................\.............................\cmap.mat
.............................\.............................\Contents.m
.............................\.............................\Examples\Classification\iris1v23.mat
.............................\.............................\........\..............\iris2v13.mat
.............................\.............................\........\..............\iris3v12.mat
.............................\.............................\........\..............\linsep.mat
.............................\.............................\........\..............\nlinsep.mat
.............................\.............................\........\Regression\example.mat
.............................\.............................\........\..........\sinc.mat
.............................\.............................\........\..........\titanium.mat
.............................\.............................\newsvm.zip
.............................\.............................\nobias.m
.............................\.............................\Optimiser\Makefile
.............................\.............................\.........\pr_loqo.c
.............................\.............................\.........\pr_loqo.h
.............................\.............................\.........\qp.c
.............................\.............................\.........\qp.dll
.............................\.............................\qp.dll
.............................\.............................\README
.............................\.............................\softmargin.m
.............................\.............................\svc.m
.............................\.............................\svcerror.m
.............................\.............................\svcinfo.m
.............................\.............................\svcoutput.m
.............................\.............................\svcplot.m
.............................\.............................\svdatanorm.m
.............................\.............................\svkernel.m
.............................\.............................\svr.m
.............................\.............................\svrerror.m
.............................\.............................\svroutput.m
.............................\.............................\svrplot.m
.............................\.............................\svtol.m
.............................\.............................\uiclass.m
.............................\.............................\uiclass.mat
.............................\.............................\uiregress.m
.............................\.............................\uiregress.mat
.............................\.............................\Examples\Classification
.............................\.............................\........\Regression
.............................\.............................\Examples
.............................\.............................\Optimiser
.............................\zhichixiangliangjisuanfa(svm)
zhichixiangliangjisuanfa(svm)