CategoryMismatchTrainTest#

class CategoryMismatchTrainTest[source]#

Find new categories in the test set.

Parameters
columnsUnion[Hashable, List[Hashable]] , default: None

Columns to check, if none are given checks all columns except ignored ones.

ignore_columnsUnion[Hashable, List[Hashable]] , default: None

Columns to ignore, if none given checks based on columns variable.

max_features_to_showint , default: 5

maximum features with new categories to show

max_new_categories_to_showint , default: 5

maximum new categories to show in feature

__init__(columns: Optional[Union[Hashable, List[Hashable]]] = None, ignore_columns: Optional[Union[Hashable, List[Hashable]]] = None, max_features_to_show: int = 5, max_new_categories_to_show: int = 5, **kwargs)[source]#
__new__(*args, **kwargs)#

Methods

CategoryMismatchTrainTest.add_condition(...)

Add new condition function to the check.

CategoryMismatchTrainTest.add_condition_new_categories_not_greater_than([...])

Add condition - require column not to have greater than given number of different new categories.

CategoryMismatchTrainTest.add_condition_new_category_ratio_not_greater_than([...])

Add condition - require column not to have greater than given ratio of instances with new categories.

CategoryMismatchTrainTest.clean_conditions()

Remove all conditions from this check instance.

CategoryMismatchTrainTest.conditions_decision(result)

Run conditions on given result.

CategoryMismatchTrainTest.finalize_check_result(...)

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

CategoryMismatchTrainTest.metadata([...])

Return check metadata.

CategoryMismatchTrainTest.name()

Name of class in split camel case.

CategoryMismatchTrainTest.params([show_defaults])

Return parameters to show when printing the check.

CategoryMismatchTrainTest.remove_condition(index)

Remove given condition by index.

CategoryMismatchTrainTest.run(train_dataset, ...)

Run check.

CategoryMismatchTrainTest.run_logic(context)

Run check.

Examples#