Move past a single accuracy number to systematically analyze where and why your classifier makes its mistakes.
## CONTEXT Aggregate metrics tell you how well a model scores but not where it fails, and the failures are where improvement lives. Real error analysis slices the confusion matrix by class, inspects misclassified examples for patterns, checks whether errors concentrate in a subgroup, and distinguishes systematic bias…
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