Mercurial > repos > bgruening > sklearn_model_fit
comparison test-data/get_params08.tabular @ 0:5e1241fd6afd 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 16:43:07 -0400 |
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| -1:000000000000 | 0:5e1241fd6afd |
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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. |