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How to customize SVM kernel parameters in Matlab

Asked by Ikra89
on 9 Jun 2013
Latest activity Commented on by behruz
on 5 Jul 2015


I want to ask about how to customize SVM kernel parameters in Matlab.

For ex: I have linear kernel, polynomial kernel, and RBF kernel with:

C = 0.2;
gamma = 0.8;
r = 0.05;
d = 3;

My question is how do I customize it using svmstruct.

1. linear: ??

2. polynomial: ??

3. RBF:

svmstruct = svmtrain(data, groups, 'Kernel_Function', 'rbf', 'RBF_Sigma', 0.2, 'BoxConstraint', 0.8);

CMIIW about how to customize RBF kernel.

I'd really appreciate if anybody could help my research. Thanks.




2 Answers

Answer by Ikra89
on 10 Jun 2013

anybody can help? :)


Answer by Ahmed
on 10 Jun 2013

Documentation given by

   help svmtrain

should give you all information you need. What is the meaning of your variable r?

1. the linear kernel has only parameter C

   svmstruct = svmtrain(data, groups, 'Kernel_Function', 'linear', 'BoxConstraint', 0.2);

2. polynomial has parameters C and polyorder

   svmstruct = svmtrain(data, groups, 'Kernel_Function', 'polynomial', 'polyorder',3,'BoxConstraint', 0.2);

3. RBF

you might have mixed up the constants C and gamma in your code


on 6 Jul 2013

Using an anonymous function of a linear kernel would be:

svmstruct = svmtrain(data, groups, ...
'Kernel_Function',@(x1,x2) x1*x2','BoxConstraint', 0.2);

Note, that your kernel function must lead to a valid kernel.

on 4 Jul 2015

hi the combination of C and gamma how is implemented? in fitcsvnm or svmtrain we dont have any gamma factor how is the impact of it apllied to svm?

on 5 Jul 2015

any comment?

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