ó §ñ:i´ ãóh•SSKrSSKJr SSKJr SSKJr SSKJ r SSK J r "SS 5r S r S rg) éNé)Úcheck_consistent_length)Úcheck_matplotlib_support)Ú_get_response_values_binary)Útype_of_target)Ú_check_pos_label_consistencycó`•\rSrSrSrSSS.Sjr\SSSS.Sj5r\SSSS .S j5rS r g) Ú"_BinaryClassifierCurveDisplayMixiné zÌMixin class to be used in Displays requiring a binary classifier. The aim of this class is to centralize some validations regarding the estimator and the target and gather the response of the estimator. N)ÚaxÚnamecóº•[URRS35 SSKJn UcUR 5upAUc UR OUnXRU4$)Nz.plotr)rÚ __class__Ú__name__Úmatplotlib.pyplotÚpyplotÚsubplotsÚestimator_nameÚfigure)Úselfr r ÚpltÚ_s ÚZ/srv/projetos/modelo_ml_acdoc/venv/lib/python3.13/site-packages/sklearn/utils/_plotting.pyÚ_validate_plot_paramsÚ8_BinaryClassifierCurveDisplayMixin._validate_plot_paramssQ€Ü  D§N¡N×$;Ñ$;Ð#<¸EÐ!BÔCÝ'à ‰:Ø—L‘L“N‰EˆAà&*¡lˆt×"Ò"¸ˆØ—9‘9˜dÐ"Ð"óÚauto)Úresponse_methodÚ pos_labelr cóŒ•[URS35 UcURROUn[UUUUS9upuXuU4$)Nz.from_estimator)rr)rrrr)ÚclsÚ estimatorÚXÚyrrr Úy_preds rÚ!_validate_and_get_response_valuesÚD_BinaryClassifierCurveDisplayMixin._validate_and_get_response_valuessT€ô ! C§L¡L >°Ð!AÔBà/3©|ˆy×"Ñ"×+Ò+Àˆä7Ø Ø Ø+Øñ  шð $Ð&Ð&r)Ú sample_weightrr có•[URS35 [U5S:wa[S[U5S35e[ XU5 [ XA5nUbUOSnXE4$)Nz.from_predictionsÚbinaryz The target y is not binary. Got z type of target.Ú Classifier)rrrÚ ValueErrorrr)r!Úy_truer%r(rr s rÚ!_validate_from_predictions_paramsÚD_BinaryClassifierCurveDisplayMixin._validate_from_predictions_params,st€ô ! C§L¡L >Ð1BÐ!CÔDä ˜&Ó ! XÓ -ÜØ2´>À&Ó3IÐ2JðKðóð ô  ° Ô>Ü0°ÓCˆ àÑ'‰t¨\ˆàˆÐr©) rÚ __module__Ú __qualname__Ú__firstlineno__Ú__doc__rÚ classmethodr&r.Ú__static_attributes__r0rrr r sI†ñð +/°Tõ#ðà17À4Èdô'óð'ð à.2¸dÈôóórr có6•UbU$Uc U(aS$S$[U5(a UROUnU(a"URS5(aUSSnO$SU3nOURS5(aSUSS3nURSS5nUR 5$) a¥Validate the `score_name` parameter. If `score_name` is provided, we just return it as-is. If `score_name` is `None`, we use `Score` if `negate_score` is `False` and `Negative score` otherwise. If `score_name` is a string or a callable, we infer the name. We replace `_` by spaces and capitalize the first letter. We remove `neg_` and replace it by `"Negative"` if `negate_score` is `False` or just remove it otherwise. NzNegative scoreÚScoreÚneg_éz Negative rÚ )ÚcallablerÚ startswithÚreplaceÚ capitalize)Ú score_nameÚscoringÚ negate_scores rÚ_validate_score_namerC@sª€ðÑØÐØ ‰Þ#/ÐÐ<°WÐ<ä)1°'×):Ñ):W×%Ò%Àˆ Þ Ø×$Ñ$ V×,Ñ,Ø'¨¨˜^‘ à(¨¨ Ð5‘ Ø × "Ñ " 6× *Ñ *Ø$ Z°° ^Ð$4Ð5ˆJØ×'Ñ'¨¨SÓ1ˆ Ø×$Ñ$Ó&Ð&rcó˜•[R"[R"U55nUR5UR 5- $)zðCompute the ratio between the largest and smallest inter-point distances. A value larger than 5 typically indicates that the parameter range would better be displayed with a log scale while a linear scale would be more suitable otherwise. )ÚnpÚdiffÚsortÚmaxÚmin)ÚdatarFs rÚ_interval_max_min_ratiorK[s1€ô 7Š7”2—7’7˜4“=Ó !€DØ 8‰8‹:˜Ÿ™› Ñ "Ð"r)ÚnumpyrEÚrÚ_optional_dependenciesrÚ _responserÚ multiclassrÚ validationrr rCrKr0rrÚrRs,ðÛå%Ý<Ý2Ý&Ý4÷3ñ3òl'ó6#r