Binary Classification
One model, one set of probabilities. Moving the cut-off from 0.10 to 0.90 took precision from 0.5271 to 0.9864 and recall from 0.8869 to 0.4306.
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Logistic Regression for Binary Classification
A practical guide to logistic regression, from probability and cross-entropy to vectorized gradients and a complete NumPy implementation.