ML.EVAL.CLASSIFICATION.BRIER_SCORE_LOSS

Returns the Brier score loss.

Syntax

ML.EVAL.CLASSIFICATION.BRIER_SCORE_LOSS(y_true, y_score, sample_weight, pos_label)

Arguments

Name	Type	Default	Description
y_true	object		DataFrame or array object of ground-truth target values.
y_score	object		DataFrame or array object of predicted probabilities or decision scores (e.g. output of ML.PREDICT_PROBA or ML.PREDICT).
sample_weight	Any	None	Optional DataFrame or array object of per-sample weights. Omit for uniform weights.
pos_label	Any	1	Class to report as the positive class for binary metrics.

Examples

Examples coming soon

Working Excel formula examples for this function are not yet written.

See also

• ML.EVAL.CLASSIFICATION.ACCURACY
• ML.EVAL.CLASSIFICATION.AVERAGE_PRECISION
• ML.EVAL.CLASSIFICATION.BALANCED_ACCURACY
• ML.EVAL.CLASSIFICATION.D2_LOG_LOSS_SCORE
• ML.EVAL.CLASSIFICATION.F1
• ML.EVAL.CLASSIFICATION.JACCARD
• ML.EVAL.CLASSIFICATION.LOG_LOSS
• ML.EVAL.CLASSIFICATION.MATTHEWS_CORRCOEF
• ML.EVAL.CLASSIFICATION.PRECISION
• ML.EVAL.CLASSIFICATION.RECALL
• ML.EVAL.CLASSIFICATION.ROC_AUC
• ML.EVAL.CLASSIFICATION.TOP_K_ACCURACY