annotate test-data/get_params11.tabular @ 10:6e25381dad5c draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f031d8ddfb73cec24572648666ac44ee47f08aad
author bgruening
date Thu, 11 Aug 2022 09:36:17 +0000
parents 0985b0dd6f1a
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0985b0dd6f1a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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1 Parameter Value
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2 * memory memory: None
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3 * steps "steps: [('editednearestneighbours', EditedNearestNeighbours(kind_sel='all', n_jobs=1, n_neighbors=3,
0985b0dd6f1a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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4 random_state=None, ratio=None, return_indices=False,
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5 sampling_strategy='auto')), ('randomforestclassifier', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
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6 max_depth=None, max_features='auto', max_leaf_nodes=None,
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7 min_impurity_decrease=0.0, min_impurity_split=None,
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8 min_samples_leaf=1, min_samples_split=2,
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9 min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1,
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10 oob_score=False, random_state=None, verbose=0,
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11 warm_start=False))]"
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12 @ editednearestneighbours "editednearestneighbours: EditedNearestNeighbours(kind_sel='all', n_jobs=1, n_neighbors=3,
0985b0dd6f1a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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13 random_state=None, ratio=None, return_indices=False,
0985b0dd6f1a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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14 sampling_strategy='auto')"
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15 @ randomforestclassifier "randomforestclassifier: RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
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16 max_depth=None, max_features='auto', max_leaf_nodes=None,
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17 min_impurity_decrease=0.0, min_impurity_split=None,
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18 min_samples_leaf=1, min_samples_split=2,
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19 min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1,
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20 oob_score=False, random_state=None, verbose=0,
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21 warm_start=False)"
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22 @ editednearestneighbours__kind_sel editednearestneighbours__kind_sel: 'all'
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23 * editednearestneighbours__n_jobs editednearestneighbours__n_jobs: 1
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24 @ editednearestneighbours__n_neighbors editednearestneighbours__n_neighbors: 3
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25 @ editednearestneighbours__random_state editednearestneighbours__random_state: None
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26 @ editednearestneighbours__ratio editednearestneighbours__ratio: None
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27 @ editednearestneighbours__return_indices editednearestneighbours__return_indices: False
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28 @ editednearestneighbours__sampling_strategy editednearestneighbours__sampling_strategy: 'auto'
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29 @ randomforestclassifier__bootstrap randomforestclassifier__bootstrap: True
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30 @ randomforestclassifier__class_weight randomforestclassifier__class_weight: None
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31 @ randomforestclassifier__criterion randomforestclassifier__criterion: 'gini'
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32 @ randomforestclassifier__max_depth randomforestclassifier__max_depth: None
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33 @ randomforestclassifier__max_features randomforestclassifier__max_features: 'auto'
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34 @ randomforestclassifier__max_leaf_nodes randomforestclassifier__max_leaf_nodes: None
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35 @ randomforestclassifier__min_impurity_decrease randomforestclassifier__min_impurity_decrease: 0.0
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36 @ randomforestclassifier__min_impurity_split randomforestclassifier__min_impurity_split: None
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37 @ randomforestclassifier__min_samples_leaf randomforestclassifier__min_samples_leaf: 1
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38 @ randomforestclassifier__min_samples_split randomforestclassifier__min_samples_split: 2
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39 @ randomforestclassifier__min_weight_fraction_leaf randomforestclassifier__min_weight_fraction_leaf: 0.0
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40 @ randomforestclassifier__n_estimators randomforestclassifier__n_estimators: 'warn'
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41 * randomforestclassifier__n_jobs randomforestclassifier__n_jobs: 1
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42 @ randomforestclassifier__oob_score randomforestclassifier__oob_score: False
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43 @ randomforestclassifier__random_state randomforestclassifier__random_state: None
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44 * randomforestclassifier__verbose randomforestclassifier__verbose: 0
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45 @ randomforestclassifier__warm_start randomforestclassifier__warm_start: False
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46 Note: @, searchable params in searchcv too.