How to compute SFS(Sequential feature selection) with "multiple class" SVM?

I can use sequentialfs function to compute the SFS with two-class SVM.(means the binary output [0 1])
below is my code:
%% x=features, y=binary response. c = cvpartition(y,'k',10); opts = statset('display','iter'); [fs,history] = sequentialfs(fun,x,y,'cv',c,'options',opts)
function err = SVM_class_fun(xTrain, yTrain, xTest, yTest) model = svmtrain(xTrain, yTrain, 'Kernel_Function', 'polynomial','polyorder',2, 'boxconstraint', 1); err = sum(svmclassify(model, xTest) ~= yTest); end
my issue is how to cumpute SFS when y is not binary.
I can't try it successfully,
help me, thanks!

回答 (1 件)

Nisar Ahmed
Nisar Ahmed 2018 年 9 月 20 日

0 投票

You can use Mdl = fitcecoc(xTrain, yTrain) instead of svmtrain for model construction.

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質問済み:

2016 年 4 月 14 日

回答済み:

2018 年 9 月 20 日

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