Mercurial > repos > bgruening > sklearn_label_encoder
diff test-data/get_params08.tabular @ 0:3b6ee54eb7e2 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
| author | bgruening |
|---|---|
| date | Sat, 01 May 2021 00:57:35 +0000 |
| parents | |
| children |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/get_params08.tabular Sat May 01 00:57:35 2021 +0000 @@ -0,0 +1,24 @@ + Parameter Value +* memory memory: None +* steps "steps: [('featureagglomeration', FeatureAgglomeration(affinity='euclidean', compute_full_tree='auto', + connectivity=None, linkage='ward', memory=None, n_clusters=3, + pooling_func=<function mean at 0x1123f1620>)), ('adaboostclassifier', AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, + learning_rate=1.0, n_estimators=50, random_state=None))]" +@ featureagglomeration "featureagglomeration: FeatureAgglomeration(affinity='euclidean', compute_full_tree='auto', + connectivity=None, linkage='ward', memory=None, n_clusters=3, + pooling_func=<function mean at 0x1123f1620>)" +@ adaboostclassifier "adaboostclassifier: AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, + learning_rate=1.0, n_estimators=50, random_state=None)" +@ featureagglomeration__affinity featureagglomeration__affinity: 'euclidean' +@ featureagglomeration__compute_full_tree featureagglomeration__compute_full_tree: 'auto' +@ featureagglomeration__connectivity featureagglomeration__connectivity: None +@ featureagglomeration__linkage featureagglomeration__linkage: 'ward' +* featureagglomeration__memory featureagglomeration__memory: None +@ featureagglomeration__n_clusters featureagglomeration__n_clusters: 3 +@ featureagglomeration__pooling_func featureagglomeration__pooling_func: <function mean at 0x1123f1620> +@ adaboostclassifier__algorithm adaboostclassifier__algorithm: 'SAMME.R' +@ adaboostclassifier__base_estimator adaboostclassifier__base_estimator: None +@ adaboostclassifier__learning_rate adaboostclassifier__learning_rate: 1.0 +@ adaboostclassifier__n_estimators adaboostclassifier__n_estimators: 50 +@ adaboostclassifier__random_state adaboostclassifier__random_state: None + Note: @, searchable params in searchcv too.