evalml.data_checks.OutliersDataCheck

class evalml.data_checks.OutliersDataCheck(random_state=0)

Checks if there are any outliers in input data by using an Isolation Forest to obtain the anomaly score of each index and then using IQR to determine score anomalies. Indices with score anomalies are considered outliers.

name = 'OutliersDataCheck'

Instance attributes

Methods:

__init__	Checks if there are any outliers in the input data.
validate	Checks if there are any outliers in a dataframe by using an Isolation Forest to obtain the anomaly score of each index and then using IQR to determine score anomalies.

evalml.data_checks.LabelLeakageDataCheck.validate evalml.data_checks.OutliersDataCheck.__init__