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Machine Learning Intermediate Pro

Model Evaluation Metrics

Pick, compute and defend the right metric for classification, regression and ranking

30 min read 28 views

Master the confusion matrix and its derived metrics, ROC vs precision-recall curves, log loss, calibration and ECE, cost-based threshold selection, regression and ranking metrics like NDCG, multiclass averaging, and how to tell real metric gains from noise.

Practice questions (7)

  • Reading a Confusion Matrix Under Imbalance

    Intermediate · Free
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  • ROC-AUC vs PR-AUC for a Rare-Event Model

    Intermediate
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  • Choosing a Threshold From a Cost Matrix

    Intermediate
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  • Diagnosing Calibration From a Reliability Table

    Advanced
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  • Comparing Two Rankers With NDCG and MRR

    Advanced
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See all 7 questions →

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