What are Precision, Recall, and F1-score in classification problems?

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Aravind 2025-02-28T15:14:12+00:00 1 Answer 9 views
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  1. Akshathadabbara
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    2025-02-28T15:19:56+00:00
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    • Precision (Positive Predictive Value): The proportion of correctly predicted positive instances among all predicted positives. Precision=TPTP+FPPrecision = frac{TP}{TP + FP}Precision=TP+FPTP​
    • Recall (Sensitivity): The proportion of correctly predicted positive instances among actual positives. Recall=TPTP+FNRecall = frac{TP}{TP + FN}Recall=TP+FNTP​
    • F1-Score: The harmonic mean of precision and recall, useful when class imbalance is present. F1=2×Precision×RecallPrecision+RecallF1 = 2 times frac{Precision times Recall}{Precision + Recall}F1=2×Precision+RecallPrecision×Recall​

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