Why is the base rate of the positive class critical to know?
mediumAnswer
- The base rate is the prior probability of the positive class in the population you'll deploy on.
- It sets the floor for any metric — 99% accuracy is trivial on a 1%-positive problem by always predicting negative.
- It affects PPV (precision) via Bayes rule even at fixed TPR/FPR.
- Always report the class balance with your metrics and, when the deployment base rate differs from training, calibrate probabilities or adjust the decision threshold.
Check yourself — multiple choice
- Base rate is unrelated to classifier performance
- The base rate sets the floor for accuracy and affects PPV via Bayes
- Base rate only matters for regression
- You can ignore base rate if AUC is high
Base rate determines the accuracy floor and shifts precision even at fixed TPR/FPR.
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