ZPhWrdZddlZddlmZddlmZmZddlmZGddeZ Gd d eZ dS) z+ Base class for the under-sampling method. N)Mapping)Interval StrOptions) BaseSamplerceZdZUdZdZdZdeej ddde hd e e giZ eed <d S) BaseUnderSamplerBase class for under-sampling algorithms. Warning: This class should not be used directly. Use the derive classes instead. zunder-samplinga\sampling_strategy : float, str, dict, callable, default='auto' Sampling information to sample the data set. - When ``float``, it corresponds to the desired ratio of the number of samples in the minority class over the number of samples in the majority class after resampling. Therefore, the ratio is expressed as :math:`\alpha_{us} = N_{m} / N_{rM}` where :math:`N_{m}` is the number of samples in the minority class and :math:`N_{rM}` is the number of samples in the majority class after resampling. .. warning:: ``float`` is only available for **binary** classification. An error is raised for multi-class classification. - When ``str``, specify the class targeted by the resampling. The number of samples in the different classes will be equalized. Possible choices are: ``'majority'``: resample only the majority class; ``'not minority'``: resample all classes but the minority class; ``'not majority'``: resample all classes but the majority class; ``'all'``: resample all classes; ``'auto'``: equivalent to ``'not minority'``. - When ``dict``, the keys correspond to the targeted classes. The values correspond to the desired number of samples for each targeted class. - When callable, function taking ``y`` and returns a ``dict``. The keys correspond to the targeted classes. The values correspond to the desired number of samples for each class. sampling_strategyrrightclosed>allautomajority not majority not minority_parameter_constraintsN)__name__ __module__ __qualname____doc___sampling_typerstrip_sampling_strategy_docstringrnumbersRealrrcallablerdict__annotations__\/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/imblearn/under_sampling/base.pyr r s &N$ H FHHK!R  HW\1a 8 8 8 JRRR S S    $Dr#r ceZdZUdZdZdZdeej ddde hd e e giZ eed <d S) BaseCleaningSamplerr zclean-samplingasampling_strategy : str, list or callable Sampling information to sample the data set. - When ``str``, specify the class targeted by the resampling. Note the the number of samples will not be equal in each. Possible choices are: ``'majority'``: resample only the majority class; ``'not minority'``: resample all classes but the minority class; ``'not majority'``: resample all classes but the majority class; ``'all'``: resample all classes; ``'auto'``: equivalent to ``'not minority'``. - When ``list``, the list contains the classes targeted by the resampling. - When callable, function taking ``y`` and returns a ``dict``. The keys correspond to the targeted classes. The values correspond to the desired number of samples for each class. r rr r r>rrrrrrN)rrrrrrrrrrrlistrrr r!r"r#r$r&r&Js &N$ . FHH/!4  HW\1a 8 8 8 JRRR S S    $Dr#r&) rrcollections.abcrsklearn.utils._param_validationrrbaserr r&r"r#r$r+s ######@@@@@@@@88888{888v)))))+)))))r#