0Ph(dZddlmZmZddlZddlmZddlm Z m Z m Z m Z m Z ddlmZmZddlmZdd lmZdd lmZdd lmZ dd Zdd ZGdde e eZdZGdde eeZdS)z)Base class for ensemble-based estimators.)ABCMetaabstractmethodN)effective_n_jobs) BaseEstimatorMetaEstimatorMixinclone is_classifier is_regressor)Bunchcheck_random_state)get_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 V/var/www/html/test/jupyter/venv/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) r sorted get_paramsendswithrandintnpiinfoint32max set_params)rr&to_setkeys r!_set_random_statesr4+s8&l33L Fi***5566GG . CLL1A$B$B &..rx/A/A/EFFF3K ' &&v&&&&&''cfeZdZdZe d deddZd dZd dZd Z d Z d Z dS) 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. N ) n_estimatorsestimator_paramsc0||_||_||_dSN)rr9r:)selfrr9r:s r!__init__zBaseEnsemble.__init__ls!#( 0r5c>|j|j|_dS||_dS)zMCheck the base estimator. Sets the `estimator_` attributes. N)r estimator_)r=defaults r!_validate_estimatorz BaseEnsemble._validate_estimator}s$ > %"nDOOO%DOOOr5Tctj}|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#3SSSr5Nr()r r@r1r:r4 estimators_append)r=rJr&rs` r!_make_estimatorzBaseEnsemble._make_estimators $/**  TTSSSST=RSSSTTT  # y, 7 7 7  /   # #I . . .r5c*t|jS)z0Return the number of estimators in the ensemble.)lenrIr=s r!__len__zBaseEnsemble.__len__s4#$$$r5c|j|S)z.Return the index'th estimator in the ensemble.)rI)r=indexs r! __getitem__zBaseEnsemble.__getitem__s&&r5c*t|jS)z0Return iterator over estimators in the ensemble.)iterrIrNs r!__iter__zBaseEnsemble.__iter__sD$%%%r5r<)TN) r __module__ __qualname____doc__rtupler>rBrKrOrRrUr(r5r!r7r7Qs4 1 1 1 1 1^ 1 &&&&"%%%'''&&&&&r5r7) metaclassc&tt||}tj|||zt}|d||zxxdz cc<tj|}||dg|zfS)z;Private function used to partition estimators between jobs.)dtypeNr)minrr-fullintcumsumtolist)r9n_jobsn_estimators_per_jobstartss r!_partition_estimatorsrfs!&))< 8 8F76<6+AMMM0<&00111Q6111 Y+ , ,F '..001# 2G GGr5cjeZdZdZedZedZdZfdZ d fd Z fdZ 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_`. c>tdit|jS)zDictionary to access any fitted sub-estimators by name. Returns ------- :class:`~sklearn.utils.Bunch` r()r dict estimatorsrNs r!named_estimatorsz+_BaseHeterogeneousEnsemble.named_estimatorss"--tDO,,---r5c||_dSr<rk)r=rks r!r>z#_BaseHeterogeneousEnsemble.__init__s $r5c 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(rFests r! zB_BaseHeterogeneousEnsemble._validate_estimators..s&@@cC6M@@@@@@r5zHAll estimators are dropped. At least one is required to be an estimator.rqz The estimator {} should be a {}.) rMrk ValueErrorzip_validate_namesanyr r rrr)r=namesrk has_estimatoris_estimator_typerss r!_validate_estimatorsz/_BaseHeterogeneousEnsemble._validate_estimatorss t  1 $ $@  1z U###@@Z@@@@@  &  .;4-@-@RMMl  Cf}}%6%6s%;%;} 6== .0A0J1220N j  r5c :tjdi||S)a Set the parameters of an estimator from the ensemble. Valid parameter keys can be listed with `get_params()`. Note that you can directly set the parameters of the estimators contained in `estimators`. Parameters ---------- **params : keyword arguments Specific parameters using e.g. `set_params(parameter_name=new_value)`. In addition, to setting the parameters of the estimator, the individual estimator of the estimators can also be set, or can be removed by setting them to 'drop'. Returns ------- self : object Estimator instance. rkrn)super _set_params)r=paramsrs r!r1z%_BaseHeterogeneousEnsemble.set_paramss', 33F333 r5TcJtd|S)a< Get the parameters of an estimator from the ensemble. Returns the parameters given in the constructor as well as the estimators contained within the `estimators` parameter. Parameters ---------- deep : bool, default=True Setting it to True gets the various estimators and the parameters of the estimators as well. Returns ------- params : dict Parameter and estimator names mapped to their values or parameter names mapped to their values. rkr$)r _get_params)r=r%rs r!r*z%_BaseHeterogeneousEnsemble.get_params s"&ww""_BaseHeterogeneousEnsemble.__sklearn_tags__..#s[,,:=Q69I9IQ  +55t,,,,,,r5c3pK|]1}|ddkrt|djjndV2dSr)rrsparserrs r!rtz>_BaseHeterogeneousEnsemble.__sklearn_tags__..'s[))7:!f6F6FQ  +22D))))))r5)r__sklearn_tags__allrkrrr Exception)r=tagsrs r!rz+_BaseHeterogeneousEnsemble.__sklearn_tags__ sww'')) (+,,?,,,))DO %&)))?)))&&DO " "    D    sAA44 BB)T) rrVrWrXpropertyrlrr>r}r1r*r __classcell__)rs@r!rhrhs$..X.%%^%!!!:2<<<<<<*r5rh)NNr<)rXabcrrnumpyr-joblibrbaserrr r r utilsr r utils._tagsrutils._user_interfacerutils.metadata_routingrutils.metaestimatorsrr"r4r7rfrhr(r5r!rs// ('''''''######XXXXXXXXXXXXXX--------""""""777777555555333333@D0#'#'#'#'LQ&Q&Q&Q&Q&%}Q&Q&Q&Q&h H H H~~~~~(G~~~~~~r5