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 Fscore or Fmeasure

neg_log_loss: Negative Log loss, aka logistic loss or crossentropy loss.

precision: Compute the precision

recall: Compute the recall

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