Confusion Matrix
In plain terms
A table summarizing a classifier's correct and wrong predictions.
Going deeper
A confusion matrix breaks predictions into true/false positives and negatives, revealing exactly where a model errs. It shows more than overall accuracy.
Under the hood
The basis for precision, recall, and F1; crucial when classes are imbalanced.
Examples
Classification evaluation, precision/recall, imbalanced data, model analysis.
Think of it like...
Like a report card detailing not just the grade but every type of mistake.