Evaluating Classification Models: Accuracy, Precision, Recall and F1

A model that is “95% accurate” can still be useless. Learn how to read a confusion matrix and calculate accuracy, precision, recall, false positive rate and F1 score, with fully worked examples, and how to choose the right measure for problems such as fraud detection, medical screening and spam filtering.

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