evalml.data_checks.ClassImbalanceDataCheck

class evalml.data_checks.ClassImbalanceDataCheck(threshold=0.1, min_samples=100, num_cv_folds=3)

Checks if any target labels are imbalanced beyond a threshold. Use for classification problems

name = 'ClassImbalanceDataCheck'

Methods:

__init__	Check if any of the target labels are imbalanced, or if the number of values for each target
validate	Checks if any target labels are imbalanced beyond a threshold for binary and multiclass problems

Class Inheritance

evalml.data_checks.NoVarianceDataCheck.validate evalml.data_checks.ClassImbalanceDataCheck.__init__