Metrics for Evaluating Machine Learning Models – Classification
Confusion Matrix Let’s say we have a binary classifier cats and non- cats, we have 1100 test images, 1000 non cats, 100 cats. The output of the classifier is either Positive which means “cat” or Negative which means non-cat. The following is called confusion matrix: How to interpret these term is as follows: Correctness of […]
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