How to perform cross-validation using svmtrain polynomial function?

I am using SVM polynomial kernel(Statistics tool box) with order ranging from 3 to 9 (Say). When we perform cross validation with rbf function, we intend to determine sigma and C values. With the best sigma and cost factor value the trained network is tested on the test set. Do we determine cost function and sigma as well while performing cross-validation using SVM polynomial kernel? The commands that I intend to use are
structtr = svmtrain(z1,trainoutput,'Kernel_Function','Polynomial','Polyorder',i,'showplot',false);
grouparousallat = svmclassify(structtr,w1,'showplot',false);

回答(0 个)

类别

帮助中心File Exchange 中查找有关 MATLAB 的更多信息

提问:

2016-2-21

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by