evalml.data_checks.ClassImbalanceDataCheck.__init__

ClassImbalanceDataCheck.__init__(threshold=0.1)

Check if any of the features are likely to be ID columns.

Parameters

threshold (float) – The minimum threshold allowed for class imbalance before a warning is raised. A perfectly balanced dataset would have a threshold of (1/n_classes), ie 0.50 for binary classes. Defaults to 0.10

evalml.data_checks.ClassImbalanceDataCheck evalml.data_checks.ClassImbalanceDataCheck.validate