Accuracy alone can easily mislead the situation significantly, especially in cases of severely imbalanced data such as fraud, churn, or rare diseases. Confusion Matrix like precision, recall, F1, and ROC–AUC depict more clearly how your classifier works. Besides, you can provide the explanation of these metrics without using complex formulas. Connect With Us: WhatsApp Begin…
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