opencv - BOW with more 2-classes SVMs of one multiclass SVM -

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because opencv's forum has problem, want post question here too.

in example of bow opencv, there trained 2-classes svm classifier each class. why isn't use multi-class svm instead? if this, then, supposing have x classes, have load x svms , predict x times image.

because code large , uses large dataset, takes long doing research.

[ have managed start training first svm classifier opencv's bow example, says:

143 positive training samples; 2356 negative training samples

i wondering if not bad classifier... maybe train_auto find needed parameters not bad. think? ]


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