:iR(SrSSKJrJr SSKJr SSKrSSKJ r SSK J r J r J r JrJr SSKJrJr SS KJr SS KJr SS KJr SS KJr SS jrSSjr"SS\ \ \S9rSr"SS\ \\S9rg)z)Base class for ensemble-based estimators.)ABCMetaabstractmethod)ListN)effective_n_jobs) BaseEstimatorMetaEstimatorMixinclone is_classifier is_regressor)Bunchcheck_random_state _safe_tags)_print_elapsed_time)_routing_enabled)_BaseCompositionc[5(d0SU;a*[XE5 URXUSS9 SSS5 U$[XE5 UR"X40UD6 SSS5 U$!,(df  U$=f![aDnS[ U5;a/[SR UR R55UeeSnAff=f!,(df  U$=f)z7Private function used to fit an estimator within a job. sample_weight)rNz+unexpected keyword argument 'sample_weight'z8Underlying estimator {} does not support sample weights.)rrfit TypeErrorstrformat __class____name__) estimatorXy fit_paramsmessage_clsnamemessageexcs Y/srv/projetos/modelo_ml_acdoc/venv/lib/python3.13/site-packages/sklearn/ensemble/_base.py_fit_single_estimatorr$s   /Z"? $_> a*_2M N? ! : MM! -* -; ?>  <CHNUU!++44   ; : s? A;A)A; C ) A83A;8A;; C ?CC  CcJ[U5n0n[URSS95H`nUS:XdURS5(dM!UR [ R "[ R5R5X#'Mb U(aUR"S0UD6 gg)aeSet fixed random_state parameters for an estimator. Finds all parameters ending ``random_state`` and sets them to integers derived from ``random_state``. Parameters ---------- estimator : estimator supporting get/set_params Estimator with potential randomness managed by random_state parameters. random_state : int, RandomState instance or None, default=None Pseudo-random number generator to control the generation of the random integers. Pass an int for reproducible output across multiple function calls. See :term:`Glossary `. Notes ----- This does not necessarily set *all* ``random_state`` attributes that control an estimator's randomness, only those accessible through ``estimator.get_params()``. ``random_state``s not controlled include those belonging to: * cross-validation splitters * ``scipy.stats`` rvs Tdeep random_state__random_stateN) rsorted get_paramsendswithrandintnpiinfoint32max set_params)rr(to_setkeys r#_set_random_statesr6,s8&l3L Fi***56 . CLL1A$B$B&..rxx/A/E/EFFK7&v&c~\rSrSr%Sr/r\\\S'\ SS\ "5S.Sjj5r SSjr SS jr S rS rS rS rg) BaseEnsembleRaBase class for all ensemble classes. Warning: This class should not be used directly. Use derived classes instead. Parameters ---------- estimator : object The base estimator from which the ensemble is built. n_estimators : int, default=10 The number of estimators in the ensemble. estimator_params : list of str, default=tuple() The list of attributes to use as parameters when instantiating a new base estimator. If none are given, default parameters are used. Attributes ---------- estimator_ : estimator The base estimator from which the ensemble is grown. estimators_ : list of estimators The collection of fitted base estimators. _required_parametersN ) n_estimatorsestimator_paramsc(XlX lX0lgN)rr=r>)selfrr=r>s r#__init__BaseEnsemble.__init__ps#( 0r7cNURbURUlgXlg)z=Check the base estimator. Sets the `estimator_` attributes. N)r estimator_)rAdefaults r#_validate_estimator BaseEnsemble._validate_estimators >> %"nnDO%Or7c [UR5nUR"S0URVs0sHoD[ X5_M snD6 Ub [ X25 U(aUR RU5 U$s snf)zMake and configure a copy of the `estimator_` attribute. Warning: This method should be used to properly instantiate new sub-estimators. r*)r rEr3r>getattrr6 estimators_append)rArLr(rps r#_make_estimatorBaseEnsemble._make_estimatorss $//* TT=R=RS=R74#3 3=RST  # y 7     # #I . TsA> c,[UR5$)z0Return the number of estimators in the ensemble.)lenrKrAs r#__len__BaseEnsemble.__len__s4##$$r7c URU$)z.Return the index'th estimator in the ensemble.)rK)rAindexs r# __getitem__BaseEnsemble.__getitem__s&&r7c,[UR5$)z0Return iterator over estimators in the ensemble.)iterrKrRs r#__iter__BaseEnsemble.__iter__sD$$%%r7)rrEr>r=r@)TN)r __module__ __qualname____firstlineno____doc__r;rr__annotations__rtuplerBrGrNrSrWr[__static_attributes__r*r7r#r9r9RsW6')$s)( 1 1 1 &"%'&r7r9) metaclassc[[U5U5n[R"XU-[S9nUSX-===S- sss&[R "U5nXR 5S/UR 5-4$)z;Private function used to partition estimators between jobs.)dtypeNr)minrr/fullintcumsumtolist)r=n_jobsn_estimators_per_jobstartss r#_partition_estimatorsrpst!&)< 8F7766+AM0<01Q61 YY+ ,F ..01# 2G GGr7cn^\rSrSrSrS/r\S5r\S5r Sr U4Sjr S U4Sjjr S r S rU=r$) _BaseHeterogeneousEnsembleaIBase class for heterogeneous ensemble of learners. Parameters ---------- estimators : list of (str, estimator) tuples The ensemble of estimators to use in the ensemble. Each element of the list is defined as a tuple of string (i.e. name of the estimator) and an estimator instance. An estimator can be set to `'drop'` using `set_params`. Attributes ---------- estimators_ : list of estimators The elements of the estimators parameter, having been fitted on the training data. If an estimator has been set to `'drop'`, it will not appear in `estimators_`. estimatorsc>[S0[UR5D6$)zgDictionary to access any fitted sub-estimators by name. Returns ------- :class:`~sklearn.utils.Bunch` r*)r dictrtrRs r#named_estimators+_BaseHeterogeneousEnsemble.named_estimatorss-tDOO,--r7cXlgr@rt)rArts r#rB#_BaseHeterogeneousEnsemble.__init__s$r7c [UR5S:Xa [S5e[UR6upUR U5 [ SU55nU(d [S5e[ U5(a[ O[nUHTnUS:wdM U"U5(aM[SRURRURSS55e X4$)NrzfInvalid 'estimators' attribute, 'estimators' should be a non-empty list of (string, estimator) tuples.c3*# UH oS:gv M g7f)dropNr*.0ests r# B_BaseHeterogeneousEnsemble._validate_estimators..s@Zc6MZszHAll estimators are dropped. At least one is required to be an estimator.r~z The estimator {} should be a {}.) rQrt ValueErrorzip_validate_namesanyr r rrr)rAnamesrt has_estimatoris_estimator_typers r#_validate_estimators/_BaseHeterogeneousEnsemble._validate_estimatorss t 1 $@  1 U#@Z@@ &  .;4-@-@MlCf}%6s%;%; 6== ..0A0J0J120N  r7c (>[TU]"S0UD6 U$)a3 Set the parameters of an estimator from the ensemble. Valid parameter keys can be listed with `get_params()`. Note that you can directly set the parameters of the estimators contained in `estimators`. Parameters ---------- **params : keyword arguments Specific parameters using e.g. `set_params(parameter_name=new_value)`. In addition, to setting the parameters of the estimator, the individual estimator of the estimators can also be set, or can be removed by setting them to 'drop'. Returns ------- self : object Estimator instance. rz)super _set_params)rAparamsrs r#r3%_BaseHeterogeneousEnsemble.set_paramss, 3F3 r7c >[TU]SUS9$)a Get the parameters of an estimator from the ensemble. Returns the parameters given in the constructor as well as the estimators contained within the `estimators` parameter. Parameters ---------- deep : bool, default=True Setting it to True gets the various estimators and the parameters of the estimators as well. Returns ------- params : dict Parameter and estimator names mapped to their values or parameter names mapped to their values. rtr&)r _get_params)rAr'rs r#r,%_BaseHeterogeneousEnsemble.get_paramss&w".(s5*C47q6V3C 3q6";/M*s)+F)preserves_dtyper)allrt Exception)rArs r# _more_tags%_BaseHeterogeneousEnsemble._more_tags&sG ??I$&I>>  I  s # 22rz)T)rr]r^r_r`r;propertyrwrrBrr3r,rrc __classcell__)rs@r#rrrrsQ$)> ..%%!:2<* ? ?r7rr)NNr@) r`abcrrtypingrnumpyr/joblibrbaserr r r r utilsr r utils._tagsrutils._user_interfacerutils.metadata_routingrutils.metaestimatorsrr$r6r9rprrr*r7r#rsk/ (#XX-$753@D0#'LT&%}T&n H{?(G{?r7