The confusion matrix
Example: Confusion matrix evaluates classification performance using predicted and actual values
Definition
The "confusion matrix" is a table used in data science and AI to evaluate the performance of a classification model by comparing predicted labels against actual labels, helping to visualize correct and incorrect predictions for each class.
Etymology
The term "confusion matrix" originates from the idea of 'confusion' in classification tasks, where the model may mix up or confuse different classes. The matrix format was adopted to systematically represent these confusions between actual and predicted classes.
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"The confusion matrix" appears in the Vocaplus list "English - Data & AI - (A1-C2) - set 1", containing 110 commonly used words.
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