Model evaluation guide

Model evaluation guide

Choose metrics, calculate a confusion matrix, and compare models using a repeatable evaluation protocol.

1. Define the positive class, threshold, and consequences of false positives and false negatives.
2. Compare the candidate and a simple baseline on the same split; keep test data out of tuning.
3. Report sample size, class distribution, failure cases, and any undefined metrics.