ML.EVAL.CLASSIFICATION.ROC_AUC¶
Returns the ROC AUC classification score.
Syntax¶
ML.EVAL.CLASSIFICATION.ROC_AUC(y_true, y_score, average, sample_weight, max_fpr, multi_class, labels)
Arguments¶
| Name | Type | Default | Description |
|---|---|---|---|
| y_true | Any | Positional argument 1 | |
| y_score | Any | Positional argument 2 | |
| average | Any | "macro" | Positional argument 3 |
| sample_weight | Any | None | Positional argument 4 |
| max_fpr | Any | None | Positional argument 5 |
| multi_class | Any | "raise" | Positional argument 6 |
| labels | Any | None | Positional argument 7 |
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.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.TOP_K_ACCURACY