Mercurial > repos > bgruening > sklearn_feature_selection
view test-data/get_params09.tabular @ 36:d84b3a229a52 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author | bgruening |
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date | Wed, 09 Aug 2023 13:21:19 +0000 |
parents | ec25331946b8 |
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Parameter Value * memory memory: None * steps "steps: [('relieff', ReliefF(discrete_threshold=10, n_features_to_select=3, n_jobs=1, n_neighbors=100, verbose=False)), ('randomforestregressor', RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False))]" @ relieff "relieff: ReliefF(discrete_threshold=10, n_features_to_select=3, n_jobs=1, n_neighbors=100, verbose=False)" @ randomforestregressor "randomforestregressor: RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False)" @ relieff__discrete_threshold relieff__discrete_threshold: 10 @ relieff__n_features_to_select relieff__n_features_to_select: 3 * relieff__n_jobs relieff__n_jobs: 1 @ relieff__n_neighbors relieff__n_neighbors: 100 * relieff__verbose relieff__verbose: False @ randomforestregressor__bootstrap randomforestregressor__bootstrap: True @ randomforestregressor__criterion randomforestregressor__criterion: 'mse' @ randomforestregressor__max_depth randomforestregressor__max_depth: None @ randomforestregressor__max_features randomforestregressor__max_features: 'auto' @ randomforestregressor__max_leaf_nodes randomforestregressor__max_leaf_nodes: None @ randomforestregressor__min_impurity_decrease randomforestregressor__min_impurity_decrease: 0.0 @ randomforestregressor__min_impurity_split randomforestregressor__min_impurity_split: None @ randomforestregressor__min_samples_leaf randomforestregressor__min_samples_leaf: 1 @ randomforestregressor__min_samples_split randomforestregressor__min_samples_split: 2 @ randomforestregressor__min_weight_fraction_leaf randomforestregressor__min_weight_fraction_leaf: 0.0 @ randomforestregressor__n_estimators randomforestregressor__n_estimators: 'warn' * randomforestregressor__n_jobs randomforestregressor__n_jobs: 1 @ randomforestregressor__oob_score randomforestregressor__oob_score: False @ randomforestregressor__random_state randomforestregressor__random_state: None * randomforestregressor__verbose randomforestregressor__verbose: 0 @ randomforestregressor__warm_start randomforestregressor__warm_start: False Note: @, searchable params in searchcv too.