annotate test-data/get_params03.tabular @ 10:5dd3f77a2257 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8850f42c2c3763e614f7454c9c006f3d2ff572c0
author bgruening
date Fri, 27 May 2022 12:01:34 +0000
parents 734c66aa945a
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734c66aa945a "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: [('robustscaler', RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
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4 with_scaling=True)), ('xgbclassifier', XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
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5 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
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6 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
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7 n_jobs=1, nthread=None, objective='binary:logistic', random_state=0,
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8 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
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9 silent=True, subsample=1))]"
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10 @ robustscaler "robustscaler: RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
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11 with_scaling=True)"
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12 @ xgbclassifier "xgbclassifier: XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
734c66aa945a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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13 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
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14 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
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15 n_jobs=1, nthread=None, objective='binary:logistic', random_state=0,
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16 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
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17 silent=True, subsample=1)"
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18 @ robustscaler__copy robustscaler__copy: True
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19 @ robustscaler__quantile_range robustscaler__quantile_range: (25.0, 75.0)
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20 @ robustscaler__with_centering robustscaler__with_centering: True
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21 @ robustscaler__with_scaling robustscaler__with_scaling: True
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22 @ xgbclassifier__base_score xgbclassifier__base_score: 0.5
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23 @ xgbclassifier__booster xgbclassifier__booster: 'gbtree'
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24 @ xgbclassifier__colsample_bylevel xgbclassifier__colsample_bylevel: 1
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25 @ xgbclassifier__colsample_bytree xgbclassifier__colsample_bytree: 1
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26 @ xgbclassifier__gamma xgbclassifier__gamma: 0
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27 @ xgbclassifier__learning_rate xgbclassifier__learning_rate: 0.1
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28 @ xgbclassifier__max_delta_step xgbclassifier__max_delta_step: 0
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29 @ xgbclassifier__max_depth xgbclassifier__max_depth: 3
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30 @ xgbclassifier__min_child_weight xgbclassifier__min_child_weight: 1
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31 @ xgbclassifier__missing xgbclassifier__missing: nan
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32 @ xgbclassifier__n_estimators xgbclassifier__n_estimators: 100
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33 * xgbclassifier__n_jobs xgbclassifier__n_jobs: 1
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34 * xgbclassifier__nthread xgbclassifier__nthread: None
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35 @ xgbclassifier__objective xgbclassifier__objective: 'binary:logistic'
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36 @ xgbclassifier__random_state xgbclassifier__random_state: 0
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37 @ xgbclassifier__reg_alpha xgbclassifier__reg_alpha: 0
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38 @ xgbclassifier__reg_lambda xgbclassifier__reg_lambda: 1
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39 @ xgbclassifier__scale_pos_weight xgbclassifier__scale_pos_weight: 1
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40 @ xgbclassifier__seed xgbclassifier__seed: None
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41 @ xgbclassifier__silent xgbclassifier__silent: True
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42 @ xgbclassifier__subsample xgbclassifier__subsample: 1
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43 Note: @, searchable params in searchcv too.