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What is a confusion matrix, and give a concrete case where accuracy is misleading.

A confusion matrix is the 2x2 of right and wrong predictions per class, and it is the reason a 99% accurate fraud model can be useless. The worked imbalance example, and how reading the matrix as precision and recall fixes the lie.

Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

A confusion matrix is the 2x2 of right and wrong predictions per class, and it is the reason a 99% accurate fraud model can be useless. The worked imbalance example, and how reading the matrix as precision and recall fixes the lie.

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FEDITOR'S NOTE

The screen is whether the candidate can both lay out the four cells (TP/FP/FN/TN) correctly AND produce a sharp imbalance example where high accuracy hides a model that catches nothing, then recover precision and recall from the matrix. Strong candidates pick a rare-positive domain (fraud, disease, churn), compute the trivial 'always predict majority' baseline, and explain why that baseline scores high accuracy while having zero recall. The reserved follow-up is 'so what do you report instead': precision, recall, F1, or PR-AUC, chosen by which error costs more.

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