Created
January 21, 2018 05:01
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Find the cut off point of a binary classification python
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| def Find_Optimal_Cutoff(target, predicted): | |
| """ Find the optimal probability cutoff point for a classification model related to event rate | |
| Parameters | |
| ---------- | |
| target : Matrix with dependent or target data, where rows are observations | |
| predicted : Matrix with predicted data, where rows are observations | |
| Returns | |
| ------- | |
| list type, with optimal cutoff value | |
| """ | |
| fpr, tpr, threshold = roc_curve(target, predicted) | |
| i = np.arange(len(tpr)) | |
| roc = pd.DataFrame({'tf' : pd.Series(tpr-(1-fpr), index=i), 'threshold' : pd.Series(threshold, index=i)}) | |
| roc_t = roc.ix[(roc.tf-0).abs().argsort()[:1]] | |
| return list(roc_t['threshold']) |
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Any source code of this function available
plz hepl