Mercurial > repos > bgruening > sklearn_ensemble

comparison test-data/get_params09.tabular @ 24:e94395c672bd draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
author bgruening
date Tue, 14 May 2019 18:15:12 -0400
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23:39ae276e75d9 24:e94395c672bd
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.