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Machine Learning · Model evaluation metrics
Confusion matrix, accuracy and why it fails on imbalanced data, precision, recall, F1, ROC-AUC, and regression metrics.
- On imbalanced data a model can be 99% accurate by always predicting the majority class.
- Precision asks how many flagged cases were real; recall asks how many real cases were flagged.