ML.EVAL.CLASSIFICATION.AVERAGE_PRECISION

Returns the average precision classification score.

Syntax

ML.EVAL.CLASSIFICATION.AVERAGE_PRECISION(y_true, y_score, average, pos_label, sample_weight)

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).
average	Any	"macro"	How to average across classes. One of 'micro', 'macro', 'weighted', 'samples', or leave blank for per-class scores.
pos_label	Any	1	Class to report as the positive class for binary metrics.
sample_weight	Any	None	Optional DataFrame or array object of per-sample weights. Omit for uniform weights.

Examples

Examples coming soon

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

See also

• ML.EVAL.CLASSIFICATION.ACCURACY
• ML.EVAL.CLASSIFICATION.BALANCED_ACCURACY
• ML.EVAL.CLASSIFICATION.BRIER_SCORE_LOSS
• 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