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What is a confusion matrix used for?

Answer and explanation

Correct answer: To summarize the correct and incorrect predictions of a classification model

A confusion matrix is an evaluation table that compares actual class labels with the classes predicted by a classifier. Its cells count true positives, true negatives, false positives, and false negatives, allowing a teacher or analyst to inspect both correct decisions and types of error. It can support measures such as accuracy, precision, and recall, but it does not create training examples, reduce features, or fill missing values.

Related tags

Artificial IntelligenceConfusion MatrixClassificationModel EvaluationUnit 2: Data Science MethodologyUnit 2 Data Science MethodologyPart B: Subject Specific SkillsPart B Subject Specific Skills

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