使用libsvm的serialfs选择功能 | 使用libsvm的serialfs选择功能

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问题描述

我想使用matlab工具箱进行特征选择.有一个很好的函数，称为sequencefs，可以很好地完成工作.但是，我无法将其与LibSVM函数集成以执行功能选择.它可以与KnnClassify一起正常工作，请有人帮我.这是KnnClassify的代码:

I want to use matlab toolbox to do feature selection. there is one good function there called sequentialfs that does a good job. However, I could not integrate it with LibSVM function to perform features selection. It works fine with KnnClassify, can somebody help me please. here is the code for KnnClassify:

fun1 = @(XT，yT，Xt，yt)...

fun1 = @(XT,yT,Xt,yt)...

    (sum((yt ~= knnclassify(Xt,XT,yT,5))));

[fs，history] =顺序fs(fun1，data，label，'cv'，c，'options'，opts，'direction'，'forward');

[fs,history] = sequentialfs(fun1,data,label,'cv',c,'options',opts,'direction','forward');

推荐答案

您需要包装libsvm函数，以在特定功能集上训练和测试SVM.我建议在单独的.m文件中编写内容(尽管原则上我认为它可以在匿名函数中使用).像这样:

You'll need to wrap the libsvm functions to train and test an SVM on a particular featureset. I'd suggest writing things in a separate .m file (though in priciple I think it could go in an anonymous function). Something like:

function err = svmwrapper(xTrain, yTrain, xTest, yTest)
  model = svmtrain(yTrain, xTrain, <svm parameters>);
  err = sum(svmpredict(yTest, xTest, model) ~= yTest);
end

，然后您可以通过以下方式呼叫sequentialfs:

and then you can call sequentialfs with:

[fs history] = sequentialfs(@svmwrapper, ...);

(您可能需要检查svmtrain的参数的顺序，我永远不记得它们应该是哪种方式).

(You may need to check the order of the arguments to svmtrain, I can never remember which way round they should be).

想法是svmwrapper将训练SVM并在测试集上返回其错误.

The idea is that svmwrapper will train an SVM and return its error on the test set.

匿名等效项为:

svmwrapper = @(xTrain, yTrain, xTest, yTest)sum(svmpredict(yTest, xTest, svmtrain(yTrain, xTrain, <svm parameters>) ~= yTest);

看起来不太好.

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