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Stop 07 · Model Evaluation & TuningTopics · 3/8

ROC-AUC Curve

Part of the Data Science Roadmap

In short

A curve plotting true positive rate against false positive rate across different classification thresholds — AUC (area under the curve) summarizes overall model discriminative power in one number.

How to learn this

  1. 1Plot an ROC curve for a trained classification model.
  2. 2Learn what an AUC of 0.5 versus 1.0 versus a specific value like 0.85 actually means.
  3. 3Understand ROC-AUC can be misleading on severely imbalanced datasets — check precision-recall curves too.

More topics at this stop

Classification Metrics (Accuracy, Precision, Recall, F1)Confusion MatrixRegression Metrics (MAE, RMSE, R²)Hyperparameter Tuning (Grid / Random Search)Regularization (L1 / L2)Ensemble MethodsModel Selection Strategy

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