IdentifierLeakage#

class IdentifierLeakage[source]#

Check if identifiers (Index/Date) can be used to predict the label.

Parameters
ppscore_paramsany , default: None

dictionary containing params to pass to ppscore predictor

__init__(ppscore_params=None, **kwargs)[source]#
__new__(*args, **kwargs)#

Methods

IdentifierLeakage.add_condition(name, ...)

Add new condition function to the check.

IdentifierLeakage.add_condition_pps_not_greater_than([...])

Add condition - require columns not to have a greater pps than given max.

IdentifierLeakage.clean_conditions()

Remove all conditions from this check instance.

IdentifierLeakage.conditions_decision(result)

Run conditions on given result.

IdentifierLeakage.finalize_check_result(...)

Finalize the check result by adding the check instance and processing the conditions.

IdentifierLeakage.metadata([with_doc_link])

Return check metadata.

IdentifierLeakage.name()

Name of class in split camel case.

IdentifierLeakage.params([show_defaults])

Return parameters to show when printing the check.

IdentifierLeakage.remove_condition(index)

Remove given condition by index.

IdentifierLeakage.run(dataset[, model])

Run check.

IdentifierLeakage.run_logic(context[, ...])

Run check.

Examples#