§ «PƒiKã ó*—ddlZddlmZddlmZmZmZmZmZddl m Z m Z eeegdgddddddddœ eeggd ¢dd d gdddd œgZ ej ejejejejgd d dgdddddd œej ejejejejgd gdddddd d ¦«¦«d œgZej de ¦«e d„¦«¦«Zej de¦«e d„¦«¦«ZdS)éN)Úmetrics)ÚBaggingClassifierÚBaggingRegressorÚIsolationForestÚStackingClassifierÚStackingRegressor)Úassert_docstring_consistencyÚskip_if_no_numpydocÚ max_samplesFz4The number of samples to draw from X to train each.*) ÚobjectsÚinclude_paramsÚexclude_paramsÚ include_attrsÚ exclude_attrsÚinclude_returnsÚexclude_returnsÚdescr_regex_patternÚ ignore_types)ÚcvÚn_jobsÚ passthroughÚverboseTÚfinal_estimator_)r r rrrrrrÚaverageÚ 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 \(only meaningful for multilabel classification where this differs from :func:`accuracy_score`\)\.Úcasecó—tdi|¤ŽdS)z@Check docstrings parameters consistency between related classes.N©©r ©rs ú‡/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/sklearn/tests/test_docstring_parameters_consistency.pyÚ test_class_docstring_consistencyr#fó€õ!Ð(Ð( 4Ð(Ð(Ð(Ð(Ð(ócó—tdi|¤ŽdS)zBCheck docstrings parameters consistency between related functions.Nrr r!s r"Ú#test_function_docstring_consistencyr'mr$r%)ÚpytestÚsklearnrÚsklearn.ensemblerrrrrÚsklearn.utils._testingr r Ú!CLASS_DOCSTRING_CONSISTENCY_CASESÚprecision_recall_fscore_supportÚf1_scoreÚ fbeta_scoreÚprecision_scoreÚ recall_scoreÚjoinÚsplitÚ$FUNCTION_DOCSTRING_CONSISTENCY_CASESÚmarkÚ parametrizer#r'rr%r"úr7s)ðð€ € € àÐÐÐÐÐðððððððððððððððUÐTÐTÐTÐTÐTÐTÐTð&Ð'7¸ÐIØ(˜/ØØØØ ØØVØ&ð ð ð'Ð(9Ð:ØDÐDÐDØØØ,Ð-Ø ØØ#ð ð ð%Ð!ð6 Ô 3Ø Ô Ø Ô Ø Ô #Ø Ô ð  ðØ$ oÐ6ØØØ ØØ#ððð$ Ô 3Ø Ô Ø Ô Ø Ô #Ø Ô ð  ð%˜+ØØØØ ØØ"Ÿxšxð.÷.Še‰gŒgñ3 ô ð)ð)ð#;(Ð$ð|„×Ò˜Ð!BÑCÔCØð)ð)ñÔñDÔCð)ð „×Ò˜Ð!EÑFÔFØð)ð)ñÔñGÔFð)ð)ð)r%