WholeDatasetDrift

class WholeDatasetDrift

Calculate drift between the entire train and test datasets using a model trained to distinguish between them.

Deprecated since version 0.9: The WholeDatasetDrift check is deprecated and will be removed in the 0.11 version. Please use the MultivariateDrift check instead.

__init__(n_top_columns: int = 3, min_feature_importance: float = 0.05, max_num_categories_for_display: int = 10, show_categories_by: str = 'largest_difference', n_samples: int = 10000, random_state: int = 42, test_size: float = 0.3, min_meaningful_drift_score: float = 0.05, **kwargs)

__new__(*args, **kwargs)

Methods

WholeDatasetDrift.add_condition(name, ...)	Add new condition function to the check.
WholeDatasetDrift.add_condition_overall_drift_value_less_than([...])	Add condition.
WholeDatasetDrift.clean_conditions()	Remove all conditions from this check instance.
WholeDatasetDrift.conditions_decision(result)	Run conditions on given result.
WholeDatasetDrift.config([include_version, ...])	Return check configuration (conditions' configuration not yet supported).
WholeDatasetDrift.from_config(conf[, ...])	Return check object from a CheckConfig object.
WholeDatasetDrift.from_json(conf[, ...])	Deserialize check instance from JSON string.
WholeDatasetDrift.metadata([with_doc_link])	Return check metadata.
WholeDatasetDrift.name()	Name of class in split camel case.
WholeDatasetDrift.params([show_defaults])	Return parameters to show when printing the check.
WholeDatasetDrift.remove_condition(index)	Remove given condition by index.
WholeDatasetDrift.run(train_dataset, ...[, ...])	Run check.
WholeDatasetDrift.run_logic(context)	Run check.
WholeDatasetDrift.to_json([indent, ...])	Serialize check instance to JSON string.

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MultivariateDrift.to_json

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WholeDatasetDrift.add_condition