Mercurial > repos > bgruening > sklearn_stacking_ensemble_models

comparison test-data/get_params05.tabular @ 7:a2e4a45c6083 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 6bb8bb56f44769dcba665de057c35d74ac89e196"
author bgruening
date Mon, 16 Dec 2019 08:14:20 -0500
parents fcc5eaaec401
children
comparison
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6:fb424213e9dd 7:a2e4a45c6083
1 Parameter Value 1 Parameter Value
2 * memory memory: None 2 @ bootstrap bootstrap: True
3 * steps "steps: [('randomforestregressor', RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, 3 @ criterion criterion: 'mse'
4 max_features='auto', max_leaf_nodes=None, 4 @ max_depth max_depth: None
5 min_impurity_decrease=0.0, min_impurity_split=None, 5 @ max_features max_features: 'auto'
6 min_samples_leaf=1, min_samples_split=2, 6 @ max_leaf_nodes max_leaf_nodes: None
7 min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=1, 7 @ min_impurity_decrease min_impurity_decrease: 0.0
8 oob_score=False, random_state=42, verbose=0, warm_start=False))]" 8 @ min_impurity_split min_impurity_split: None
9 @ randomforestregressor "randomforestregressor: RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, 9 @ min_samples_leaf min_samples_leaf: 1
10 max_features='auto', max_leaf_nodes=None, 10 @ min_samples_split min_samples_split: 2
11 min_impurity_decrease=0.0, min_impurity_split=None, 11 @ min_weight_fraction_leaf min_weight_fraction_leaf: 0.0
12 min_samples_leaf=1, min_samples_split=2, 12 @ n_estimators n_estimators: 100
13 min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=1, 13 * n_jobs n_jobs: 1
14 oob_score=False, random_state=42, verbose=0, warm_start=False)" 14 @ oob_score oob_score: False
15 @ randomforestregressor__bootstrap randomforestregressor__bootstrap: True 15 @ random_state random_state: 42
16 @ randomforestregressor__criterion randomforestregressor__criterion: 'mse' 16 * verbose verbose: 0
17 @ randomforestregressor__max_depth randomforestregressor__max_depth: None 17 @ warm_start warm_start: False
18 @ randomforestregressor__max_features randomforestregressor__max_features: 'auto' 18 Note: @, params eligible for search in searchcv tool.
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.