Dear Huthaifa

SVM classifier when is used with RBF kernel is very sensitive to the kernel parameters, i.e. the kernel parameters must be finely tuned. 

When using Matlab built-in SVM model trainer (fitcecoc), it can set the parameters automatically if it is said to. For example:

• svmParams = templateSVM('KernelFunction','rbf', 'KernelScale', 'auto', 'Standardize', 1);
• svmModel = fitcecoc(trainData, trainLabels, 'Learners', svmParams, 'Coding', 'onevsall');

I have attached a full example, too.

I hope it helps.

Best 

Fardin

Dear Fardin,

Thank you very much for your help, your code works fine and it is really helpful.

May I ask you how can I find the best  C and sigma for my model??

And how can I give the fitcecoc this parameters (C and sigma).

Best, 

Huthaifa