Scoring metrics

Regression metrics

  • explained_variance: Explained variance regression score function

  • mean_absolute_error: Mean absolute error regression loss

  • mean_squared_error: Mean squared error regression loss

  • mean_squared_log_error: Mean squared logarithmic error regression loss

  • median_absolute_error: Median absolute error regression loss

  • r2: R^2 (coefficient of determination) regression score function.

Classification metrics

  • accuracy: Accuracy classification score.

  • average_precision: Compute average precision (AP) from prediction scores

  • brier_score_loss: Compute the Brier score.

  • f1_score: Compute the F1 score, also known as balanced F-score or F-measure

  • neg_log_loss: Negative Log loss, aka logistic loss or cross-entropy loss.

  • precision: Compute the precision

  • recall: Compute the recall

  • roc_auc: Compute Area Under the Curve (AUC) using the trapezoidal rule