Mercurial > repos > bgruening > scipy_sparse
diff test-data/get_params09.tabular @ 29:5b8d4d35c605 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
author | bgruening |
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date | Tue, 14 May 2019 17:59:56 -0400 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/get_params09.tabular Tue May 14 17:59:56 2019 -0400 @@ -0,0 +1,39 @@ + 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.