Mercurial > repos > bgruening > sklearn_lightgbm
comparison test-data/get_params08.tabular @ 0:13226b2ddfb4 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
author | bgruening |
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date | Wed, 22 Jan 2020 07:51:20 -0500 |
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-1:000000000000 | 0:13226b2ddfb4 |
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1 Parameter Value | |
2 * memory memory: None | |
3 * steps "steps: [('featureagglomeration', FeatureAgglomeration(affinity='euclidean', compute_full_tree='auto', | |
4 connectivity=None, linkage='ward', memory=None, n_clusters=3, | |
5 pooling_func=<function mean at 0x1123f1620>)), ('adaboostclassifier', AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, | |
6 learning_rate=1.0, n_estimators=50, random_state=None))]" | |
7 @ featureagglomeration "featureagglomeration: FeatureAgglomeration(affinity='euclidean', compute_full_tree='auto', | |
8 connectivity=None, linkage='ward', memory=None, n_clusters=3, | |
9 pooling_func=<function mean at 0x1123f1620>)" | |
10 @ adaboostclassifier "adaboostclassifier: AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, | |
11 learning_rate=1.0, n_estimators=50, random_state=None)" | |
12 @ featureagglomeration__affinity featureagglomeration__affinity: 'euclidean' | |
13 @ featureagglomeration__compute_full_tree featureagglomeration__compute_full_tree: 'auto' | |
14 @ featureagglomeration__connectivity featureagglomeration__connectivity: None | |
15 @ featureagglomeration__linkage featureagglomeration__linkage: 'ward' | |
16 * featureagglomeration__memory featureagglomeration__memory: None | |
17 @ featureagglomeration__n_clusters featureagglomeration__n_clusters: 3 | |
18 @ featureagglomeration__pooling_func featureagglomeration__pooling_func: <function mean at 0x1123f1620> | |
19 @ adaboostclassifier__algorithm adaboostclassifier__algorithm: 'SAMME.R' | |
20 @ adaboostclassifier__base_estimator adaboostclassifier__base_estimator: None | |
21 @ adaboostclassifier__learning_rate adaboostclassifier__learning_rate: 1.0 | |
22 @ adaboostclassifier__n_estimators adaboostclassifier__n_estimators: 50 | |
23 @ adaboostclassifier__random_state adaboostclassifier__random_state: None | |
24 Note: @, searchable params in searchcv too. |