IdentifierLabelCorrelation

class IdentifierLabelCorrelation

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)

__new__(*args, **kwargs)

Methods

IdentifierLabelCorrelation.add_condition(...)	Add new condition function to the check.
IdentifierLabelCorrelation.add_condition_pps_less_or_equal([...])	Add condition - require columns' pps to be less or equal to threshold.
IdentifierLabelCorrelation.clean_conditions()	Remove all conditions from this check instance.
IdentifierLabelCorrelation.conditions_decision(result)	Run conditions on given result.
IdentifierLabelCorrelation.config()	Return check configuration (conditions' configuration not yet supported).
IdentifierLabelCorrelation.from_config(conf)	Return check object from a CheckConfig object.
IdentifierLabelCorrelation.metadata([...])	Return check metadata.
IdentifierLabelCorrelation.name()	Name of class in split camel case.
IdentifierLabelCorrelation.params([...])	Return parameters to show when printing the check.
IdentifierLabelCorrelation.remove_condition(index)	Remove given condition by index.
IdentifierLabelCorrelation.run(dataset[, ...])	Run check.
IdentifierLabelCorrelation.run_logic(...)	Run check.

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DominantFrequencyChange.run_logic

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IdentifierLabelCorrelation.add_condition