evalml.objectives.AUC¶

class
evalml.objectives.
AUC
[source]¶ AUC score for binary classification.

name
= 'AUC'¶

greater_is_better
= True¶

perfect_score
= 1.0¶

positive_only
= False¶

problem_types
= [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>]¶

score_needs_proba
= True¶
Methods
Initialize self.
Calculate the percent difference between scores.
Apply a learned threshold to predicted probabilities to get predicted classes.
Computes the relative value of the provided predictions compared to the actual labels, according a specified metric
Learn a binary classification threshold which optimizes the current objective.
Returns a numerical score indicating performance based on the differences between the predicted and actual values.
Validates the input based on a few simple checks.
