UgR(dZddlmZmZddlmZddlZddlm Z ddl m Z m Z m Z mZmZddlmZmZdd lmZdd lmZdd lmZdd lmZ dd ZddZGdde e eZdZGdde eeZdS)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)_BaseCompositionctsd|vr t||5||||ddddn #1swxYwYn#t$rD}dt |vr-td|jj|d}~wwxYwt||5|j||fi|dddn #1swxYwY|S)z7Private function used to fit an estimator within a job. sample_weight)rNz+unexpected keyword argument 'sample_weight'z8Underlying estimator {} does not support sample weights.)rrfit TypeErrorstrformat __class____name__) estimatorXy fit_paramsmessage_clsnamemessageexcs U/var/www/surfInsights/venv3-11/lib/python3.11/site-packages/sklearn/ensemble/_base.py_fit_single_estimatorr$s   ./Z"?"? $_g>> O O a*_2M NNN O O O O O O O O O O O O O O O   <CHHNUU!+4   !' : : . . IM!Q - -* - - - . . . . . . . . . . . . . . . sLAA AAAAA B)%?B$$B)<CCCc>t|}i}t|dD]V}|dks|dr9|t jt jj||<W|r|j di|dSdS)aSet 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&l33L Fi***5566GG . CLL1A$B$B &..rx/A/A/EFFF3K ' &&v&&&&&''ceZdZUdZgZeeed<e d de ddZ d dZ dd Z d Z d Zd ZdS) BaseEnsembleaBase 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_paramsc0||_||_||_dSN)rr<r=)selfrr<r=s r#__init__zBaseEnsemble.__init__ps!#( 0r7c>|j|j|_dS||_dS)zMCheck the base estimator. Sets the `estimator_` attributes. N)r estimator_)r@defaults r#_validate_estimatorz BaseEnsemble._validate_estimators$ > %"nDOOO%DOOOr7Tctj}|jdifdjD|t |||rj||S)zMake and configure a copy of the `estimator_` attribute. Warning: This method should be used to properly instantiate new sub-estimators. c2i|]}|t|Sr*)getattr).0pr@s r# z0BaseEnsemble._make_estimator..s%SSS74#3#3SSSr7Nr*)r rCr3r=r6 estimators_append)r@rMr(rs` r#_make_estimatorzBaseEnsemble._make_estimators $/**  TTSSSST=RSSSTTT  # y, 7 7 7  /   # #I . . .r7c*t|jS)z0Return the number of estimators in the ensemble.)lenrLr@s r#__len__zBaseEnsemble.__len__s4#$$$r7c|j|S)z.Return the index'th estimator in the ensemble.)rL)r@indexs r# __getitem__zBaseEnsemble.__getitem__s&&r7c*t|jS)z0Return iterator over estimators in the ensemble.)iterrLrQs r#__iter__zBaseEnsemble.__iter__sD$%%%r7r?)TN)r __module__ __qualname____doc__r:rr__annotations__rtuplerArErNrRrUrXr*r7r#r9r9Rs6')$s)((( 1 1 1 1 1^ 1 &&&&"%%%'''&&&&&r7r9) metaclassc&tt||}tj|||zt}|d||zxxdz cc<tj|}||dg|zfS)z;Private function used to partition estimators between jobs.)dtypeNr)minrr/fullintcumsumtolist)r<n_jobsn_estimators_per_jobstartss r#_partition_estimatorsrjs!&))< 8 8F76<6+AMMM0<&00111Q6111 Y+ , ,F '..001# 2G GGr7cleZdZdZdgZedZedZdZ fdZ d fd Z d Z xZ S) _BaseHeterogeneousEnsembleaBase 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>tdit|jS)zDictionary to access any fitted sub-estimators by name. Returns ------- :class:`~sklearn.utils.Bunch` r*)r dictrmrQs r#named_estimatorsz+_BaseHeterogeneousEnsemble.named_estimatorss"--tDO,,---r7c||_dSr?rm)r@rms r#rAz#_BaseHeterogeneousEnsemble.__init__s $r7c t|jdkrtdt|j\}}||t d|D}|stdt |rt nt}|D]M}|dkrE||s:td|j j |j ddN||fS)NrzfInvalid 'estimators' attribute, 'estimators' should be a non-empty list of (string, estimator) tuples.c3"K|] }|dkV dS)dropNr*rIests r# zB_BaseHeterogeneousEnsemble._validate_estimators..s&@@cC6M@@@@@@r7zHAll estimators are dropped. At least one is required to be an estimator.ruz The estimator {} should be a {}.) rPrm ValueErrorzip_validate_namesanyr r rrr)r@namesrm has_estimatoris_estimator_typerws r#_validate_estimatorsz/_BaseHeterogeneousEnsemble._validate_estimatorss t  1 $ $@  1z U###@@Z@@@@@  &  .;4-@-@RMMl  Cf}}%6%6s%;%;} 6== .0A0J1220N j  r7c :tjdi||S)a 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. rmrr)super _set_params)r@paramsrs r#r3z%_BaseHeterogeneousEnsemble.set_paramss', 33F333 r7TcJtd|S)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. rmr&)r _get_params)r@r'rs r#r,z%_BaseHeterogeneousEnsemble.get_paramss"&ww"".(sZ47q6V3C3C 3q6"";//r7F)preserves_dtyper)allrm Exception)r@rs r# _more_tagsz%_BaseHeterogeneousEnsemble._more_tags&sn ?II   III   $&I>>>s ! 00)T)rrYrZr[r:propertyrprrArr3r,r __classcell__)rs@r#rlrls$)> ..X.%%^%!!!:2<<<<<<* ? ? ? ? ? ? ?r7rl)NNr?) r[abcrrtypingrnumpyr/joblibrbaserr r r r utilsr r utils._tagsrutils._user_interfacerutils.metadata_routingrutils.metaestimatorsrr$r6r9rjrlr*r7r#rs// ('''''''######XXXXXXXXXXXXXX--------$$$$$$777777555555333333@D0#'#'#'#'LT&T&T&T&T&%}T&T&T&T&n H H H{?{?{?{?{?(G{?{?{?{?{?{?r7