Mercurial > repos > bgruening > sklearn_searchcv
view test-data/get_params04.tabular @ 23:c6ae57f774c6 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8850f42c2c3763e614f7454c9c006f3d2ff572c0
author | bgruening |
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date | Fri, 27 May 2022 11:33:30 +0000 |
parents | 1c4a241bef5c |
children |
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Parameter Value * memory memory: None * steps "steps: [('selectfrommodel', SelectFromModel(estimator=AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0, n_estimators=50, random_state=None), max_features=None, norm_order=1, prefit=False, threshold=None)), ('linearsvc', LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True, intercept_scaling=1, loss='squared_hinge', max_iter=1000, multi_class='ovr', penalty='l2', random_state=None, tol=0.0001, verbose=0))]" @ selectfrommodel "selectfrommodel: SelectFromModel(estimator=AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0, n_estimators=50, random_state=None), max_features=None, norm_order=1, prefit=False, threshold=None)" @ linearsvc "linearsvc: LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True, intercept_scaling=1, loss='squared_hinge', max_iter=1000, multi_class='ovr', penalty='l2', random_state=None, tol=0.0001, verbose=0)" @ selectfrommodel__estimator__algorithm selectfrommodel__estimator__algorithm: 'SAMME.R' @ selectfrommodel__estimator__base_estimator selectfrommodel__estimator__base_estimator: None @ selectfrommodel__estimator__learning_rate selectfrommodel__estimator__learning_rate: 1.0 @ selectfrommodel__estimator__n_estimators selectfrommodel__estimator__n_estimators: 50 @ selectfrommodel__estimator__random_state selectfrommodel__estimator__random_state: None @ selectfrommodel__estimator "selectfrommodel__estimator: AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0, n_estimators=50, random_state=None)" @ selectfrommodel__max_features selectfrommodel__max_features: None @ selectfrommodel__norm_order selectfrommodel__norm_order: 1 @ selectfrommodel__prefit selectfrommodel__prefit: False @ selectfrommodel__threshold selectfrommodel__threshold: None @ linearsvc__C linearsvc__C: 1.0 @ linearsvc__class_weight linearsvc__class_weight: None @ linearsvc__dual linearsvc__dual: True @ linearsvc__fit_intercept linearsvc__fit_intercept: True @ linearsvc__intercept_scaling linearsvc__intercept_scaling: 1 @ linearsvc__loss linearsvc__loss: 'squared_hinge' @ linearsvc__max_iter linearsvc__max_iter: 1000 @ linearsvc__multi_class linearsvc__multi_class: 'ovr' @ linearsvc__penalty linearsvc__penalty: 'l2' @ linearsvc__random_state linearsvc__random_state: None @ linearsvc__tol linearsvc__tol: 0.0001 * linearsvc__verbose linearsvc__verbose: 0 Note: @, searchable params in searchcv too.