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An expected fraction of rejected null hypotheses that are falsely rejected, i.e. the fraction of significant findings that are actually not true. One method to control FDR in multiple testing is Benjamini-Hochberg procedure.
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Loss function for neural network to reduce false positives
I am trying to train a network to keep false positive as low as possible. I do not mind if I don't have extremely high accuracy, but I want the false positives to be within 5%.
Are there any existin …