ROC, AUC, and Thresholds
Judging ranking quality across cutoffs.
Models Output Probabilities
Most classifiers do not just say yes or no. They give a probability, like 0.73, and you decide where to draw the line. 🎚️
probs = model.predict_proba(X)[:, 1]The Decision Threshold
A threshold turns a probability into a label. Above it means positive, below means negative. The default 0.5 is just one choice.
y_pred = probs >= 0.5All lessons in this course
- Regression Metrics: MAE, MSE, R2
- The Confusion Matrix Decoded
- Precision, Recall, and F1
- ROC, AUC, and Thresholds