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 | 1 | initial version |
looking at the implementation -- it seems you need [-1,1] labels for this ;)
| | 2 | No.2 Revision |
looking at the implementation -- it seems you need [-1,1] labels for this ;)
if all your truth_data is positive, there is no need to train anything, because all your samples are on the "same side" of the support vector
(it's also a binary classifier only, unlike cv::SVM it canhandle only 2 classes)
