How to compute SFS(Sequential feature selection) with "multiple class" SVM？
显示 更早的评论
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 个）
Nisar Ahmed
2018-9-20
0 个投票
You can use Mdl = fitcecoc(xTrain, yTrain) instead of svmtrain for model construction.
类别
在 帮助中心 和 File Exchange 中查找有关 Dimensionality Reduction and Feature Extraction 的更多信息
2016-4-14
2018-9-20
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
