annotate test-data/get_params12.tabular @ 3:72c0d2747dc9 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d6333e7294e67be5968a41f404b66699cad4ae53"
author bgruening
date Thu, 07 Nov 2019 05:43:19 -0500
parents f96efab83b65
children 6b94d76a1397
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f96efab83b65 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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1 Parameter Value
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2 * memory memory: None
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3 * steps "steps: [('rfe', RFE(estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
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4 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
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5 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
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6 n_jobs=1, nthread=None, objective='reg:linear', random_state=0,
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7 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
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8 silent=True, subsample=1),
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9 n_features_to_select=None, step=1, verbose=0))]"
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10 @ rfe "rfe: RFE(estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
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11 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
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12 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
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13 n_jobs=1, nthread=None, objective='reg:linear', random_state=0,
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14 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
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15 silent=True, subsample=1),
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16 n_features_to_select=None, step=1, verbose=0)"
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17 @ rfe__estimator__base_score rfe__estimator__base_score: 0.5
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18 @ rfe__estimator__booster rfe__estimator__booster: 'gbtree'
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19 @ rfe__estimator__colsample_bylevel rfe__estimator__colsample_bylevel: 1
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20 @ rfe__estimator__colsample_bytree rfe__estimator__colsample_bytree: 1
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21 @ rfe__estimator__gamma rfe__estimator__gamma: 0
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22 @ rfe__estimator__learning_rate rfe__estimator__learning_rate: 0.1
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23 @ rfe__estimator__max_delta_step rfe__estimator__max_delta_step: 0
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24 @ rfe__estimator__max_depth rfe__estimator__max_depth: 3
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25 @ rfe__estimator__min_child_weight rfe__estimator__min_child_weight: 1
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26 @ rfe__estimator__missing rfe__estimator__missing: nan
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27 @ rfe__estimator__n_estimators rfe__estimator__n_estimators: 100
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28 * rfe__estimator__n_jobs rfe__estimator__n_jobs: 1
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29 * rfe__estimator__nthread rfe__estimator__nthread: None
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30 @ rfe__estimator__objective rfe__estimator__objective: 'reg:linear'
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31 @ rfe__estimator__random_state rfe__estimator__random_state: 0
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32 @ rfe__estimator__reg_alpha rfe__estimator__reg_alpha: 0
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33 @ rfe__estimator__reg_lambda rfe__estimator__reg_lambda: 1
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34 @ rfe__estimator__scale_pos_weight rfe__estimator__scale_pos_weight: 1
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35 @ rfe__estimator__seed rfe__estimator__seed: None
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36 @ rfe__estimator__silent rfe__estimator__silent: True
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37 @ rfe__estimator__subsample rfe__estimator__subsample: 1
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38 @ rfe__estimator "rfe__estimator: XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
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39 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
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40 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
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41 n_jobs=1, nthread=None, objective='reg:linear', random_state=0,
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42 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
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43 silent=True, subsample=1)"
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44 @ rfe__n_features_to_select rfe__n_features_to_select: None
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45 @ rfe__step rfe__step: 1
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46 * rfe__verbose rfe__verbose: 0
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47 Note: @, searchable params in searchcv too.