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SVM trainAuto v/s train

asked 2016-12-02 09:32:15 -0500

Akash Garg gravatar image

I am using SVM for facial expression recognition using opencv. I trained my model using normal train function however my model accuracy is not too good. I want to optimize it using cross-validation testing. For it think i would need to use trainAuto. Does tainAuto first train and then perform cross-validation testing or do i need to use train and then tainAuto?? Thanks in advance!

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answered 2016-12-04 21:44:34 -0500

sammoes gravatar image

You don't need to first use train. TrainAuto searches the SVM parameter space using cross validation. It doesn't search the parameter space (if you have any) of your features. Try stepping into trainAuto with a debugger to see what it gets you. I think the main problem is that trainAuto can still give you a local optimum. See the libsvm website for advice on a good approach.

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Asked: 2016-12-02 09:32:15 -0500

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Last updated: Dec 04 '16