Hi, I have a doubt regarding the AUC score. I would say that AUC should be 1 only if all the samples in class 0 have score 0 and all the samples in class 1 have score 1.
With the roc_auc_score function I get the value 1 for separable classes. Isn't this wrong? Or maybe I am confused? x = np.arange(0, 1, .1) y = np.array([0] * 7 + [1] * 3) roc_auc_score(y, x) # = 1 In this example if I classify 1 x>.3 than I do not have a 0 error. So I think that auc should not be 1. Let me know. thanks, Luca -- Sent by mobile phone
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