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‎sklearn/metrics/ranking.py

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@@ -412,7 +412,6 @@ def precision_recall_curve(y_true, probas_pred, pos_label=None,
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sample_weight=sample_weight)
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precision = tps / (tps + fps)
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# recall = tps / tps[-1]
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recall = np.ones(tps.size) if tps[-1] == 0 else tps / tps[-1]
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# stop when full recall attained

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