Classification Evaluation and Error Analysis

By the end of this module you can evaluate a classifier beyond accuracy - per-class performance, confusion between specific pairs, and the error analysis that tells you which failures actually matter.

Units

1. Unit 07.00: Accuracy on imbalanced classes tells you nothing
2. Unit 07.01: The confusion matrix and which cell costs most
3. Unit 07.02: Choosing a threshold from the cost of each error
4. Unit 07.03: Looking at the mistakes the model was most sure about
5. Unit 07.04: Slices where the model is quietly worse

Module work

• Activity
• Knowledge check
• Summary