o ZÆ&i¼ã @sddlZddlmZddlmZmZmZmZmZddl m Z m Z eeegdgddddddddœ eeggd ¢dd d gdddd œgZ ej ejejejejgd d dgdddddd œej ejejejejgd gdddddd d ¡¡d œgZej de ¡e dd„ƒƒZej de¡e dd„ƒƒZdS)éN)Úmetrics)ÚBaggingClassifierÚBaggingRegressorÚIsolationForestÚStackingClassifierÚStackingRegressor)Úassert_docstring_consistencyÚskip_if_no_numpydocZ max_samplesFz4The number of samples to draw from X to train each.*) ÚobjectsÚinclude_paramsÚexclude_paramsÚ include_attrsÚ exclude_attrsÚinclude_returnsÚexclude_returnsÚdescr_regex_patternZ ignore_types)ZcvZn_jobsZ passthroughÚverboseTZfinal_estimator_)r r r r rrrrZaverageZ zero_divisionú a/This parameter is required for multiclass/multilabel targets\. If ``None``, the metrics for each class are returned\. Otherwise, this determines the type of averaging performed on the data: ``'binary'``: Only report results for the class specified by ``pos_label``\. This is applicable only if targets \(``y_\{true,pred\}``\) are binary\. ``'micro'``: Calculate metrics globally by counting the total true positives, false negatives and false positives\. ``'macro'``: Calculate metrics for each label, and find their unweighted mean\. This does not take label imbalance into account\. ``'weighted'``: Calculate metrics for each label, and find their average weighted by support \(the number of true instances for each label\)\. This alters 'macro' to account for label imbalance; it can result in an F-score that is not between precision and recall\.[\s\w]*\.* ``'samples'``: Calculate metrics for each instance, and find their average \(only meaningful for multilabel classification where this differs from :func:`accuracy_score`\)\.ÚcasecCótdi|¤ŽdS)z@Check docstrings parameters consistency between related classes.N©©r©rrrú^C:\wamp64\www\opt\env\Lib\site-packages\sklearn/tests/test_docstring_parameters_consistency.pyÚ test_class_docstring_consistencyfórcCr)zBCheck docstrings parameters consistency between related functions.NrrrrrrÚ#test_function_docstring_consistencymrr)ZpytestZsklearnrZsklearn.ensemblerrrrrZsklearn.utils._testingrr Z!CLASS_DOCSTRING_CONSISTENCY_CASESZprecision_recall_fscore_supportZf1_scoreZ fbeta_scoreZprecision_scoreZ recall_scoreÚjoinÚsplitZ$FUNCTION_DOCSTRING_CONSISTENCY_CASESÚmarkZ parametrizerrrrrrÚs| ÷ øôûòûçòï >