Use confusion matrix to choose model metric

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This is a easy difficulty Statistics & Math question, commonly asked during Technical Screen rounds at Microsoft.

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This question is commonly asked for Data Scientist candidates at Microsoft during technical interviews.

Question

Use confusion matrix to choose model metric

PracHub · Accepted Answer

This question evaluates understanding of confusion matrix components, mapping Type I/Type II errors to false positives/negatives, selection and interpretation of classification metrics (accuracy, precision/recall, F1, ROC-AUC, PR-AUC, calibration), threshold choice under asymmetric costs, and identification of practical pitfalls like class imbalance, data leakage, shifting base rates, and calibration issues. It is commonly asked in Statistics & Math interviews for Data Scientist roles to assess the ability to translate model performance into business impact, testing both conceptual understanding and practical application of evaluation and cost-sensitive decision-making.

Use confusion matrix to choose model metric

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Use confusion matrix to choose model metric

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