Precision, Recall & F1

easy
Unit 1 · Classification I0/2 to milestone

Implement classification_report(y_true, y_pred) for binary labels (0/1). Return a dict with keys "precision", "recall", "f1" and "accuracy".

If a denominator is zero, the metric is 0.0.

P=TPTP+FP,R=TPTP+FN,F1=2PRP+RP = \frac{TP}{TP + FP}, \quad R = \frac{TP}{TP + FN}, \quad F_1 = \frac{2PR}{P + R}
#metrics#classification2 visible + 1 hidden tests
ML Engineer Foundations· 4 of 19
Next in path: Multiclass Confusion Matrix & Macro-F1
solution.py · Python 3.13
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Precision, Recall & F1 · TechGradify