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Machine Learning

Confusion Matrix

Machine Learning· Foundational

Definition

A table summarizing the performance of a classification model by showing the counts of true positives, true negatives, false positives, and false negatives. From the confusion matrix, key metrics like accuracy, precision, recall, and F1 score are derived. Essential for understanding where a model makes specific types of errors.

Tags

#evaluation#classification#metrics#false-positives#false-negatives
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