MatlabSVM工具箱快速入手简易教程上课讲义

1、Good is good, but better carries it.精益求精，善益求善。MatlabSVM工具箱快速入手简易教程-SVM工具箱快速入手简易教程(byfaruto)一.matlab自带的函数(matlab帮助文件里的例子)只有较新版本的matlab中有这两个SVM的函数=svmtrainsvmclassify=简要语法规则=svmtrainTrainsupportvectormachineclassifierSyntaxSVMStruct=svmtrain(Training,Group)SVMStruct=svmtrain(.,Kernel_Function,Kernel_F

2、unctionValue,.)SVMStruct=svmtrain(.,RBF_Sigma,RBFSigmaValue,.)SVMStruct=svmtrain(.,Polyorder,PolyorderValue,.)SVMStruct=svmtrain(.,Mlp_Params,Mlp_ParamsValue,.)SVMStruct=svmtrain(.,Method,MethodValue,.)SVMStruct=svmtrain(.,QuadProg_Opts,QuadProg_OptsValue,.)SVMStruct=svmtrain(.,SMO_Opts,SMO_OptsValu

3、e,.)SVMStruct=svmtrain(.,BoxConstraint,BoxConstraintValue,.)SVMStruct=svmtrain(.,Autoscale,AutoscaleValue,.)SVMStruct=svmtrain(.,Showplot,ShowplotValue,.)-svmclassifyClassifydatausingsupportvectormachineSyntaxGroup=svmclassify(SVMStruct,Sample)Group=svmclassify(SVMStruct,Sample,Showplot,ShowplotValu

4、e)=实例研究=loadfisheriris%载入matlab自带的数据有关数据的信息可以自己到UCI查找,这是UCI的经典数据之一,得到的数据如下图:tu1HYPERLINK/attachment.php?aid=24862&k=5efc27ffe8e1ec9b74c29268689e3889&t=1263976450¬humb=yest_blank1.jpg(7.94KB)2009-5-1219:50其中meas是150*4的矩阵代表着有150个样本每个样本有4个属性描述,species代表着这150个样本的分类.data=meas(:,1),meas(:,2);%在这里只取meas

5、的第一列和第二列,即只选取前两个属性.groups=ismember(species,setosa);%由于species分类中是有三个分类:setosa,versicolor,virginica,为了使问题简单,我们将其变为二分类问题:Setosaandnon-Setosa.train,test=crossvalind(holdOut,groups);cp=classperf(groups);%随机选择训练集合测试集有关crossvalind的使用请自己help一下其中cp作用是后来用来评价分类器的.svmStruct=svmtrain(data(train,:),groups(train)

6、,showplot,true);%使用svmtrain进行训练,得到训练后的结构svmStruct,在预测时使用.训练结果如图:tu2HYPERLINK/attachment.php?aid=24863&k=d5871b5f3333ec8c873d178965ef6484&t=1263976450¬humb=yest_blank2.jpg(26.86KB)2009-5-1219:50classes=svmclassify(svmStruct,data(test,:),showplot,true);%对于未知的测试集进行分类预测,结果如图:tu3HYPERLINK/attachment.p

7、hp?aid=24864&k=79da636571ae939195a632fa21c7c370&t=1263976450¬humb=yest_blank3.jpg(37.34KB)2009-5-1219:50classperf(cp,classes,test);cp.CorrectRateans=0.9867%分类器效果测评,就是看测试集分类的准确率的高低.二.台湾林智仁的libsvm工具箱该工具箱下载libsvm-mat-2.86-1:HYPERLINK/attachment.php?aid=24867&k=c05691426227073bc1909cb597eceacd&t=1263

8、976450t_blanklibsvm-mat-2.86-1.rar(73.75KB)HYPERLINK/attachment.php?aid=24867&k=c05691426227073bc1909cb597eceacd&t=1263976450t_blanklibsvm-mat-2.86-1.rar(73.75KB)下载次数:3732009-5-1220:02安装方法也很简单,解压文件,把当前工作目录调整到libsvm所在的文件夹下,再在setpath里将libsvm所在的文件夹加到里面.然后在命令行里输入mex-setup%选择一下编译器make这样就可以了.建议大家使用libsvm工

9、具箱,这个更好用一些.可以进行分类多类别,预测.=svmtrainsvmpredict=简要语法:Usage=matlabmodel=svmtrain(training_label_vector,training_instance_matrix,libsvm_options);-training_label_vector:Anmby1vectoroftraininglabels(typemustbedouble).-training_instance_matrix:Anmbynmatrixofmtraininginstanceswithnfeatures.Itcanbedenseorspars

10、e(typemustbedouble).-libsvm_options:AstringoftrainingoptionsinthesameformatasthatofLIBSVM.matlabpredicted_label,accuracy,decision_values/prob_estimates=svmpredict(testing_label_vector,testing_instance_matrix,model,libsvm_options);-testing_label_vector:Anmby1vectorofpredictionlabels.Iflabelsoftestdat

11、aareunknown,simplyuseanyrandomvalues.(typemustbedouble)-testing_instance_matrix:Anmbynmatrixofmtestinginstanceswithnfeatures.Itcanbedenseorsparse.(typemustbedouble)-model:Theoutputofsvmtrain.-libsvm_options:AstringoftestingoptionsinthesameformatasthatofLIBSVM.ReturnedModelStructure=实例研究:loadheart_sc

12、ale.mat%工具箱里自带的数据如图:tu4HYPERLINK/attachment.php?aid=24873&k=f40a408143396519121ed2f478a12159&t=1263976450¬humb=yest_blank4.jpg(9.36KB)2009-5-1220:08其中heart_scale_inst是样本,heart_scale_label是样本标签model=svmtrain(heart_scale_label,heart_scale_inst,-c1-g0.07);%训练样本,具体参数的调整请看帮助文件predict_label,accuracy,de

13、c_values=svmpredict(heart_scale_label,heart_scale_inst,model);%分类预测,这里把训练集当作测试集,验证效果如下:predict_label,accuracy,dec_values=svmpredict(heart_scale_label,heart_scale_inst,model);%testthetrainingdataAccuracy=86.6667%(234/270)(classification)=这回把SVM这点入门的东西都说完了,大家可以参照着上手了,有关SVM的原理我下面有个简易的PPT,是以前做项目时我做的当时我负

14、责有关SVM这一块代码实现讲解什么的,感兴趣的你可以看看,都是上手较快的东西,想要深入学习SVM,你的学习统计学习理论什么的.挺多的呢.HYPERLINK/attachment.php?aid=24876&k=fe23ad40b82e1b2d910e3bd90fc2c6bb&t=1263976450t_blankSVM.ppt(391KB)HYPERLINK/attachment.php?aid=24876&k=fe23ad40b82e1b2d910e3bd90fc2c6bb&t=1263976450t_blankSVM.ppt(391KB)下载次数:4292009-5-1220:18-有关S

15、VM和libsvm的非常好的资料,想要详细研究SVM看这个-HYPERLINK/attachment.php?aid=32035&k=7c402be507a1bc9299a7f8969efef751&t=1263976450t_blanklibsvm_guide.pdf(194.53KB)HYPERLINK/attachment.php?aid=32035&k=7c402be507a1bc9299a7f8969efef751&t=1263976450t_blanklibsvm_guide.pdf(194.53KB)下载次数:1862009-8-1914:58HYPERLINK/attachment.php?aid=32036&k=5a148648ce8445a95e0c63d9588a0dad&t=1263976450t_blanklibsvm_library.pdf(316.82KB)HYPERLINK/attachment.php?aid