Scoring metrics
Regression metrics
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explained_variance: Explained variance regression score function
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mean_absolute_error: Mean absolute error regression loss
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mean_squared_error: Mean squared error regression loss
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mean_squared_log_error: Mean squared logarithmic error regression loss
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median_absolute_error: Median absolute error regression loss
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r2: R^2 (coefficient of determination) regression score function.
Classification metrics
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accuracy: Accuracy classification score.
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average_precision: Compute average precision (AP) from prediction scores
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brier_score_loss: Compute the Brier score.
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f1_score: Compute the F1 score, also known as balanced F-score or F-measure
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neg_log_loss: Negative Log loss, aka logistic loss or cross-entropy loss.
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precision: Compute the precision
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recall: Compute the recall
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roc_auc: Compute Area Under the Curve (AUC) using the trapezoidal rule