July 1, 2023
Calculates key evaluation metrics such as accuracy, precision, recall, F1-score, and ROC-AUC to measure how well a model predicts outcomes.
Provides visual aids like learning curves, confusion matrices, and residual plots to help understand model behavior and detect issues like overfitting or underfitting.
Allows side-by-side comparison of multiple models, helping users select the best-performing model for deployment and optimization.
