Mercurial > repos > bgruening > scipy_sparse

comparison test-data/get_params05.tabular @ 24:b9ed7b774ba3 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
author bgruening
date Wed, 15 May 2019 07:43:48 -0400
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children a2da4cebc584
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23:27c0b1a050df 24:b9ed7b774ba3
1 Parameter Value
2 * memory memory: None
3 * steps "steps: [('randomforestregressor', RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,
4 max_features='auto', max_leaf_nodes=None,
5 min_impurity_decrease=0.0, min_impurity_split=None,
6 min_samples_leaf=1, min_samples_split=2,
7 min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=1,
8 oob_score=False, random_state=42, verbose=0, warm_start=False))]"
9 @ randomforestregressor "randomforestregressor: RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,
10 max_features='auto', max_leaf_nodes=None,
11 min_impurity_decrease=0.0, min_impurity_split=None,
12 min_samples_leaf=1, min_samples_split=2,
13 min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=1,
14 oob_score=False, random_state=42, verbose=0, warm_start=False)"
15 @ randomforestregressor__bootstrap randomforestregressor__bootstrap: True
16 @ randomforestregressor__criterion randomforestregressor__criterion: 'mse'
17 @ randomforestregressor__max_depth randomforestregressor__max_depth: None
18 @ randomforestregressor__max_features randomforestregressor__max_features: 'auto'
19 @ randomforestregressor__max_leaf_nodes randomforestregressor__max_leaf_nodes: None
20 @ randomforestregressor__min_impurity_decrease randomforestregressor__min_impurity_decrease: 0.0
21 @ randomforestregressor__min_impurity_split randomforestregressor__min_impurity_split: None
22 @ randomforestregressor__min_samples_leaf randomforestregressor__min_samples_leaf: 1
23 @ randomforestregressor__min_samples_split randomforestregressor__min_samples_split: 2
24 @ randomforestregressor__min_weight_fraction_leaf randomforestregressor__min_weight_fraction_leaf: 0.0
25 @ randomforestregressor__n_estimators randomforestregressor__n_estimators: 100
26 * randomforestregressor__n_jobs randomforestregressor__n_jobs: 1
27 @ randomforestregressor__oob_score randomforestregressor__oob_score: False
28 @ randomforestregressor__random_state randomforestregressor__random_state: 42
29 * randomforestregressor__verbose randomforestregressor__verbose: 0
30 @ randomforestregressor__warm_start randomforestregressor__warm_start: False
31 Note: @, searchable params in searchcv too.