Statistics and machine learning · Model evaluation
Classification precision, recall, and F1
Calculate precision, recall, and F1 from true-positive, false-positive, and false-negative counts.
Method and scope
Precision = TP/(TP+FP); recall = TP/(TP+FN); F1 = 2PR/(P+R).
Use classification precision, recall, and f1 for educational calculation or a clearly scoped arithmetic estimate. Intended for Learners, General educational use.
Inputs- True positives — 1
- False positives — 1
- False negatives — 1
SOURCE AND LIMITS
Assumptions: Counts refer to one binary class and the same evaluation set. The positive class has been defined consistently.
Limitations: Metrics can vary with dataset sampling, class definition, and decision threshold.
Method version 1.0.0 · Unit registry and result provenance are shown after calculation. This tool is limited to the documented scope.Explore related fields
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