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I am trying to choose the best threshold for a binary classification problem that maximises F1 measure. Currently, I am manually analysing the F1 measure at thresholds 0.1-0.9 in steps of 0.1. I am also plotting ROC curve using tpr and fpr. However, is there any approach to automatically select a threshold that separates the maximum number of positives examples from negative ones (or maximizes F1 measure)?

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