Module metrics 

Model-evaluation metrics for statistical learning (ISL ch 2, 4, 9).

Regression (MSE/RMSE/MAE/R²) and classification (accuracy, confusion matrix, ROC AUC, log-loss) measures over caller-owned slices. Reuses statistics::descriptive (mean) and statistics::correlation (ranking for AUC) — no re-implementation.

Re-exports

pub use classification::accuracy;

pub use classification::confusion_binary;

pub use classification::log_loss;

pub use classification::roc_auc;

pub use classification::ConfusionBinary;

pub use regression::mae;

pub use regression::mse;

pub use regression::r2_score;

pub use regression::rmse;

Modules

classification

Classification metrics — accuracy, the binary confusion matrix and its derived rates, ROC AUC (rank form, reusing the statistics ranker), and log-loss.

regression

Regression metrics — error and fit measures over caller-owned prediction slices. Reuses statistics::descriptive for the mean (no re-implementation).