Mercurial > repos > bgruening > sklearn_model_fit
comparison test-data/get_params09.tabular @ 0:734c66aa945a draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
author | bgruening |
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date | Fri, 01 Nov 2019 17:18:28 -0400 |
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-1:000000000000 | 0:734c66aa945a |
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1 Parameter Value | |
2 * memory memory: None | |
3 * steps "steps: [('relieff', ReliefF(discrete_threshold=10, n_features_to_select=3, n_jobs=1, | |
4 n_neighbors=100, verbose=False)), ('randomforestregressor', RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, | |
5 max_features='auto', max_leaf_nodes=None, | |
6 min_impurity_decrease=0.0, min_impurity_split=None, | |
7 min_samples_leaf=1, min_samples_split=2, | |
8 min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1, | |
9 oob_score=False, random_state=None, verbose=0, warm_start=False))]" | |
10 @ relieff "relieff: ReliefF(discrete_threshold=10, n_features_to_select=3, n_jobs=1, | |
11 n_neighbors=100, verbose=False)" | |
12 @ randomforestregressor "randomforestregressor: RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, | |
13 max_features='auto', max_leaf_nodes=None, | |
14 min_impurity_decrease=0.0, min_impurity_split=None, | |
15 min_samples_leaf=1, min_samples_split=2, | |
16 min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1, | |
17 oob_score=False, random_state=None, verbose=0, warm_start=False)" | |
18 @ relieff__discrete_threshold relieff__discrete_threshold: 10 | |
19 @ relieff__n_features_to_select relieff__n_features_to_select: 3 | |
20 * relieff__n_jobs relieff__n_jobs: 1 | |
21 @ relieff__n_neighbors relieff__n_neighbors: 100 | |
22 * relieff__verbose relieff__verbose: False | |
23 @ randomforestregressor__bootstrap randomforestregressor__bootstrap: True | |
24 @ randomforestregressor__criterion randomforestregressor__criterion: 'mse' | |
25 @ randomforestregressor__max_depth randomforestregressor__max_depth: None | |
26 @ randomforestregressor__max_features randomforestregressor__max_features: 'auto' | |
27 @ randomforestregressor__max_leaf_nodes randomforestregressor__max_leaf_nodes: None | |
28 @ randomforestregressor__min_impurity_decrease randomforestregressor__min_impurity_decrease: 0.0 | |
29 @ randomforestregressor__min_impurity_split randomforestregressor__min_impurity_split: None | |
30 @ randomforestregressor__min_samples_leaf randomforestregressor__min_samples_leaf: 1 | |
31 @ randomforestregressor__min_samples_split randomforestregressor__min_samples_split: 2 | |
32 @ randomforestregressor__min_weight_fraction_leaf randomforestregressor__min_weight_fraction_leaf: 0.0 | |
33 @ randomforestregressor__n_estimators randomforestregressor__n_estimators: 'warn' | |
34 * randomforestregressor__n_jobs randomforestregressor__n_jobs: 1 | |
35 @ randomforestregressor__oob_score randomforestregressor__oob_score: False | |
36 @ randomforestregressor__random_state randomforestregressor__random_state: None | |
37 * randomforestregressor__verbose randomforestregressor__verbose: 0 | |
38 @ randomforestregressor__warm_start randomforestregressor__warm_start: False | |
39 Note: @, searchable params in searchcv too. |