h{-dZddlmZmZddlmZddlZddlZddl m Z ddl m Z ddl m Z mZdd l mZdd l mZdd lmZmZmZdd lmZmZmZdd lmZddlmZ ddZddZGddeeeZdZGddeeeZ dS)z)Base class for ensemble-based estimators.)ABCMetaabstractmethod)ListN)effective_n_jobs)clone) is_classifier is_regressor) BaseEstimator)MetaEstimatorMixin)DecisionTreeRegressorBaseDecisionTreeDecisionTreeClassifier)Bunch_print_elapsed_time deprecated)check_random_state)_BaseCompositionc| t||5||||dddn #1swxYwYn#t$rD}dt|vr-td|jj|d}~wwxYwt||5|||dddn #1swxYwY|S)z7Private function used to fit an estimator within a job.N) sample_weightz+unexpected keyword argument 'sample_weight'z8Underlying estimator {} does not support sample weights.)rfit TypeErrorstrformat __class____name__) estimatorXyrmessage_clsnamemessageexcs R/var/www/html/Sam_Eipo/venv/lib/python3.11/site-packages/sklearn/ensemble/_base.py_fit_single_estimatorr$s  $_g>> A A a- @@@ A A A A A A A A A A A A A A A   <CHHNUU!+4   !' : :  MM!Q                  sFA9 A=A=A B?BB&C  C C c>t|}i}t|dD]V}|dks|dr9|t jt jj||<W|r|j di|dSdS)aSet fixed random_state parameters for an estimator. Finds all parameters ending ``random_state`` and sets them to integers derived from ``random_state``. Parameters ---------- estimator : estimator supporting get/set_params Estimator with potential randomness managed by random_state parameters. random_state : int, RandomState instance or None, default=None Pseudo-random number generator to control the generation of the random integers. Pass an int for reproducible output across multiple function calls. See :term:`Glossary `. Notes ----- This does not necessarily set *all* ``random_state`` attributes that control an estimator's randomness, only those accessible through ``estimator.get_params()``. ``random_state``s not controlled include those belonging to: * cross-validation splitters * ``scipy.stats`` rvs Tdeep random_state__random_stateN) rsorted get_paramsendswithrandintnpiinfoint32max set_params)rr(to_setkeys r#_set_random_statesr62s8&l33L Fi***5566GG . CLL1A$B$B &..rx/A/A/EFFF3K ' &&v&&&&&''ceZdZUdZgZeeed<e dde dddZ ddZ e d e d Zdd Zd ZdZdZdS) BaseEnsembleaBase class for all ensemble classes. Warning: This class should not be used directly. Use derived classes instead. Parameters ---------- estimator : object The base estimator from which the ensemble is built. n_estimators : int, default=10 The number of estimators in the ensemble. estimator_params : list of str, default=tuple() The list of attributes to use as parameters when instantiating a new base estimator. If none are given, default parameters are used. base_estimator : object, default="deprecated" Use `estimator` instead. .. deprecated:: 1.2 `base_estimator` is deprecated and will be removed in 1.4. Use `estimator` instead. Attributes ---------- estimator_ : estimator The base estimator from which the ensemble is grown. base_estimator_ : estimator The base estimator from which the ensemble is grown. .. deprecated:: 1.2 `base_estimator_` is deprecated and will be removed in 1.4. Use `estimator_` instead. estimators_ : list of estimators The collection of fitted base estimators. _required_parametersN r) n_estimatorsestimator_paramsbase_estimatorc>||_||_||_||_dSN)rr<r=r>)selfrr<r=r>s r#__init__zBaseEnsemble.__init__s)#( 0,r7c|j|jdvrtd|j|j|_dS|jdvr(t jdt |j|_dS||_dS)zMCheck the base estimator. Sets the `estimator_` attributes. N)NrzEBoth `estimator` and `base_estimator` were set. Only set `estimator`.zV`base_estimator` was renamed to `estimator` in version 1.2 and will be removed in 1.4.)rr> ValueError estimator_warningswarn FutureWarning)rAdefaults r#_validate_estimatorz BaseEnsemble._validate_estimators > %  '; ; ;W  > %"nDOOO  (< < < M*    #1DOOO%DOOOr7zoAttribute `base_estimator_` was deprecated in version 1.2 and will be removed in 1.4. Use `estimator_` instead.c|jS)z$Estimator used to grow the ensemble.)rErAs r#base_estimator_zBaseEnsemble.base_estimator_s r7Tctj}|jdifdjDt |t rlt |dddkrWt |tr|dn+t |tr|d|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).0prAs r# z0BaseEnsemble._make_estimator..s%SSS74#3#3SSSr7 max_featuresNautosqrt)rTg?r*) rrEr3r= isinstancerrPrr r6 estimators_append)rArYr(rs` r#_make_estimatorzBaseEnsemble._make_estimators $/**  TTSSSST=RSSSTTT i!1 2 2 ;y.$776AAi)?@@;((f(==== +@AA;((c(:::  # y, 7 7 7  /   # #I . . .r7c*t|jS)z0Return the number of estimators in the ensemble.)lenrXrLs r#__len__zBaseEnsemble.__len__s4#$$$r7c|j|S)z.Return the index'th estimator in the ensemble.)rX)rAindexs r# __getitem__zBaseEnsemble.__getitem__s&&r7c*t|jS)z0Return iterator over estimators in the ensemble.)iterrXrLs r#__iter__zBaseEnsemble.__iter__sD$%%%r7r@)TN)r __module__ __qualname____doc__r:rr__annotations__rtuplerBrJrpropertyrMrZr]r`rcr*r7r#r9r9Xs&&R')$s)((( -# - - - -^ -$&&&&4Z ,X  6%%%'''&&&&&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_estimatorsrvs!&))< 8 8F76<6+AMMM0<&00111Q6111 Y+ , ,F '..001# 2G GGr7cfeZdZdZdgZedZedZdZ fdZ d fd 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*)rdictryrLs r#named_estimatorsz+_BaseHeterogeneousEnsemble.named_estimatorss"--tDO,,---r7c||_dSr@ry)rArys r#rBz#_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*)rQests r# zB_BaseHeterogeneousEnsemble._validate_estimators..s&@@cC6M@@@@@@r7zHAll estimators are dropped. At least one is required to be an estimator.rz The estimator {} should be a {}.) r\ryrDzip_validate_namesanyr r rrr)rAnamesry has_estimatoris_estimator_typers 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. ryr~)super _set_params)rAparamsrs r#r3z%_BaseHeterogeneousEnsemble.set_params1s', 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. ryr&)r _get_params)rAr'rs r#r,z%_BaseHeterogeneousEnsemble.get_paramsJs"&ww"" ..X.%%^%!!!:2<<<<<<<<<rs// ('''''''######........ %%%%%% ;:::::::::&&&&&&333333HL,#'#'#'#'LG&G&G&G&G&%}G&G&G&G&T H H Hn<n<n<n<n<(Gn<n<n<n<n<n