Kdn+dZddlZddlmZmZddlmZddlZddl m Z ddl m Z m Z mZmZmZddlmZmZmZmZdd lmZ dd Zdd ZGd d e e eZdZGdde eeZdS)z)Base class for ensemble-based estimators.N)ABCMetaabstractmethod)List)effective_n_jobs) BaseEstimatorMetaEstimatorMixinclone is_classifier is_regressor)Bunch_print_elapsed_timecheck_random_state deprecated)_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 6lib/python3.11/site-packages/sklearn/ensemble/_base.py_fit_single_estimatorr!s  $_g>> A A a- @@@ A A A A A A A A A A A A A A A   <CHHNUU!+4   !' : :  MM!Q                  sFA9 A=A=A B?BB&C  C C c>t|}i}t|dD]V}|dks|dr9|t jt jj||<W|r|j di|dSdS)aSet fixed random_state parameters for an estimator. Finds all parameters ending ``random_state`` and sets them to integers derived from ``random_state``. Parameters ---------- estimator : estimator supporting get/set_params Estimator with potential randomness managed by random_state parameters. random_state : int, RandomState instance or None, default=None Pseudo-random number generator to control the generation of the random integers. Pass an int for reproducible output across multiple function calls. See :term:`Glossary `. Notes ----- This does not necessarily set *all* ``random_state`` attributes that control an estimator's randomness, only those accessible through ``estimator.get_params()``. ``random_state``s not controlled include those belonging to: * cross-validation splitters * ``scipy.stats`` rvs Tdeep random_state__random_stateN) rsorted get_paramsendswithrandintnpiinfoint32max set_params)rr%to_setkeys r _set_random_statesr3(s8&l33L Fi***5566GG . CLL1A$B$B &..rx/A/A/EFFF3K ' &&v&&&&&''ceZdZUdZgZeeed<e dde dddZ ddZ e d e d Zdd Zd ZdZdZdS) BaseEnsembleaBase class for all ensemble classes. Warning: This class should not be used directly. Use derived classes instead. Parameters ---------- estimator : object The base estimator from which the ensemble is built. n_estimators : int, default=10 The number of estimators in the ensemble. estimator_params : list of str, default=tuple() The list of attributes to use as parameters when instantiating a new base estimator. If none are given, default parameters are used. base_estimator : object, default="deprecated" Use `estimator` instead. .. deprecated:: 1.2 `base_estimator` is deprecated and will be removed in 1.4. Use `estimator` instead. Attributes ---------- estimator_ : estimator The base estimator from which the ensemble is grown. base_estimator_ : estimator The base estimator from which the ensemble is grown. .. deprecated:: 1.2 `base_estimator_` is deprecated and will be removed in 1.4. Use `estimator_` instead. estimators_ : list of estimators The collection of fitted base estimators. _required_parametersN r) n_estimatorsestimator_paramsbase_estimatorc>||_||_||_||_dSN)rr9r:r;)selfrr9r:r;s r __init__zBaseEnsemble.__init__zs)#( 0,r4c|j|jdvrtd|j|j|_dS|jdkr8t jdt |j|j|_dS||_dS||_dS)zMCheck the base estimator. Sets the `estimator_` attributes. N)NrzEBoth `estimator` and `base_estimator` were set. Only set `estimator`.rzV`base_estimator` was renamed to `estimator` in version 1.2 and will be removed in 1.4.)rr; ValueError estimator_warningswarn FutureWarning)r>defaults r _validate_estimatorz BaseEnsemble._validate_estimators > %  '; ; ;W  > %"nDOOO  L 0 0 M.    "."&"5")%DOOOr4zoAttribute `base_estimator_` was deprecated in version 1.2 and will be removed in 1.4. Use `estimator_` instead.c|jS)z$Estimator used to grow the ensemble.)rBr>s r base_estimator_zBaseEnsemble.base_estimator_s r4Tctj}|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#3SSSr4Nr')r rBr0r:r3 estimators_append)r>rRr%rs` r _make_estimatorzBaseEnsemble._make_estimators $/**  TTSSSST=RSSSTTT  # y, 7 7 7  /   # #I . . .r4c*t|jS)z0Return the number of estimators in the ensemble.)lenrQrIs r __len__zBaseEnsemble.__len__s4#$$$r4c|j|S)z.Return the index'th estimator in the ensemble.)rQ)r>indexs r __getitem__zBaseEnsemble.__getitem__s&&r4c*t|jS)z0Return iterator over estimators in the ensemble.)iterrQrIs r __iter__zBaseEnsemble.__iter__sD$%%%r4r=)TN)r __module__ __qualname____doc__r7rr__annotations__rtupler?rGrpropertyrJrSrVrYr\r'r4r r6r6Ns&&R')$s)((( -# - - - -^ -$&&&&>Z ,X  "%%%'''&&&&&r4r6) 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_estimatorsros!&))< 8 8F76<6+AMMM0<&00111Q6111 Y+ , ,F '..001# 2G GGr4cfeZdZdZdgZedZedZdZ 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')r dictrrrIs r named_estimatorsz+_BaseHeterogeneousEnsemble.named_estimatorss"--tDO,,---r4c||_dSr=rr)r>rrs r r?z#_BaseHeterogeneousEnsemble.__init__s $r4c 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')rNests r zB_BaseHeterogeneousEnsemble._validate_estimators..s&@@cC6M@@@@@@r4zHAll estimators are dropped. At least one is required to be an estimator.rzz The estimator {} should be a {}.) rUrrrAzip_validate_namesanyr r rrr)r>namesrr has_estimatoris_estimator_typer{s r _validate_estimatorsz/_BaseHeterogeneousEnsemble._validate_estimatorss t  1 $ $@  1z U###@@Z@@@@@  &  .;4-@-@RMMl  Cf}}%6%6s%;%;} 6== .0A0J1220N j  r4c :tjdi||S)a Set the parameters of an estimator from the ensemble. Valid parameter keys can be listed with `get_params()`. Note that you can directly set the parameters of the estimators contained in `estimators`. Parameters ---------- **params : keyword arguments Specific parameters using e.g. `set_params(parameter_name=new_value)`. In addition, to setting the parameters of the estimator, the individual estimator of the estimators can also be set, or can be removed by setting them to 'drop'. Returns ------- self : object Estimator instance. rrrw)super _set_params)r>paramsrs r r0z%_BaseHeterogeneousEnsemble.set_params"s', 33F333 r4TcJtd|S)a< Get the parameters of an estimator from the ensemble. Returns the parameters given in the constructor as well as the estimators contained within the `estimators` parameter. Parameters ---------- deep : bool, default=True Setting it to True gets the various estimators and the parameters of the estimators as well. Returns ------- params : dict Parameter and estimator names mapped to their values or parameter names mapped to their values. rrr#)r _get_params)r>r$rs r r)z%_BaseHeterogeneousEnsemble.get_params;s"&ww"" ..X.%%^%!!!:2<<<<<<<<<rs// ''''''''######XXXXXXXXXXXXXXNNNNNNNNNNNN333333HL,#'#'#'#'LB&B&B&B&B&%}B&B&B&B&J H H Hn<n<n<n<n<(Gn<n<n<n<n<n