On 12/30/2011 10:15 AM, Gael Varoquaux wrote: > On Fri, Dec 30, 2011 at 10:09:59AM +0100, Olivier Grisel wrote: >>> * You could use the decision function, (decision_function method of the >>> LinearSVC) although this is clearly a hack. >> Why is this a hack? ROC is only concerned with the relative positions >> of the decision threshold, not the probability normalization AFAIK, am >> I wrong? > You are right, but there is nothing that tell us that the decision > function is really related to a success probability. That said, the Platt > method used to implement predict_proba relies on a similar hack. > It might be that I haven't really understood the meaning of ROC curves, but I thought it worked like @ogrisel said. Whatever the correct method to produce a ROC curve from a linear classifier, I'm pretty sure that using the decision function is very common in the ML literature.
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