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This is the result after applying trained svm..i don't know why i got support vectors as 0's and why i got uncompressed support vectors. Can someone help me? <?xml version="1.0"?> -<opencv_storage> -<opencv_ml_svm> <format>3</format> <svmType>C_SVC</svmType> -<kernel> <type>LINEAR</type> </kernel> <C>1.</C> -<term_criteria> <epsilon>9.9999999999999995e-07</epsilon> <iterations>1000</iterations> </term_criteria> <var_count>8</var_count> <class_count>2</class_count> -<class_labels type_id="opencv-matrix"> <rows>2</rows> <cols>1</cols> <dt>i</dt> <data> … 
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I want to use euclidean distance to match the predicted support vector with the tested support vector. I need to set a distance threshold and calculate the distance between predicted label and tested label. If the calculated distance <= distance threshold, then it will be a match, else a non-match. … 
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