On Sun, 28 Oct 2018 at 09:31, Louis Abraham via scikit-learn < scikit-learn@python.org> wrote:
> Hi, > > According to > http://scikit-learn.org/0.16/developers/index.html#get-params-and-set-params > , > get_params and set_params are used to clone estimators. > sklearn.base.clone is function used for cloning. get_params and set_params are accessors to attributes of an estimator and are defined by BaseEstimator. For Pipeline and FeatureUnion, those accessors rely on the _BaseComposition which manage the access to attributes to the sub-estimators. > However, I don't understand how it is used in FeatureUnion: > `return self._get_params('transformer_list', deep=deep)` > transformer_list contain all the estimators used in the FeatureUnion, and the _BaseComposition allow you to access the parameters of each transformer. > > Why doesn't it contain other arguments like n_jobs and transformer_weights? > The first line in _get_params in _BaseCompositin will list the attributes of FeatureUnion; https://github.com/scikit-learn/scikit-learn/blob/06ac22d06f54353ea5d5bba244371474c7baf938/sklearn/utils/metaestimators.py#L26 For instance: In [5]: trans = FeatureUnion([('trans1', StandardScaler()), ('trans2', MinMaxScaler())]) In [6]: trans.get_params() Out[6]: {'n_jobs': None, 'transformer_list': [('trans1', StandardScaler(copy=True, with_mean=True, with_std=True)), ('trans2', MinMaxScaler(copy=True, feature_range=(0, 1)))], 'transformer_weights': None, 'trans1': StandardScaler(copy=True, with_mean=True, with_std=True), 'trans2': MinMaxScaler(copy=True, feature_range=(0, 1)), 'trans1__copy': True, 'trans1__with_mean': True, 'trans1__with_std': True, 'trans2__copy': True, 'trans2__feature_range': (0, 1)} Then, n_jobs and transformer_weights are accessible. > > Best > Louis > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > -- Guillaume Lemaitre INRIA Saclay - Parietal team Center for Data Science Paris-Saclay https://glemaitre.github.io/
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