About this document
Evaluation Metrics for ML Models by Wenbo Pan is a document available to read on EtoBox.
Classification vs regression problems: - Classification predicts categories/labels while regression predicts continuous variables. - Metrics for classification include accuracy, kappa, and AUC. Metrics for regression include RMSE, MAE, and R-squared. - AUC measures how well a model distinguishes between classes, with 1 being perfect and 0.5 having no discrimination ability.
- Author
- Wenbo Pan
- Language
- EN