Tag
classification
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Evaluation Classification Metrics, From the Ground Up: Precision, Recall, F1, ROC and AUC
The confusion matrix and everything that falls out of it: precision, recall, F1, specificity, the precision/recall trade-off, PR and ROC curves, and AUC, all built on one running toy example (a backyard cat-cam), with the equations, the intuition, and scikit-learn.
machine-learningmetricsclassificationevaluation
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Evaluation Multiclass and Multilabel Metrics: Micro, Macro, Weighted, and the Difference That Matters
How precision/recall/F1 scale past two classes: one-vs-rest, and the micro/macro/weighted averaging that decides whether rare classes count. Plus multilabel-specific metrics: subset accuracy, Hamming loss, and top-k, all on one running shelter-camera example, with scikit-learn.
machine-learningmetricsclassificationmultilabel
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