Mercurial > repos > bgruening > sklearn_mlxtend_association_rules

comparison test-data/get_params03.tabular @ 0:af2624d5ab32 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
author bgruening
date Sat, 01 May 2021 01:24:32 +0000
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-1:000000000000 0:af2624d5ab32
1 Parameter Value
2 * memory memory: None
3 * steps "steps: [('robustscaler', RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
4 with_scaling=True)), ('xgbclassifier', XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
5 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
6 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
7 n_jobs=1, nthread=None, objective='binary:logistic', random_state=0,
8 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
9 silent=True, subsample=1))]"
10 @ robustscaler "robustscaler: RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
11 with_scaling=True)"
12 @ xgbclassifier "xgbclassifier: XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
13 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
14 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
15 n_jobs=1, nthread=None, objective='binary:logistic', random_state=0,
16 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
17 silent=True, subsample=1)"
18 @ robustscaler__copy robustscaler__copy: True
19 @ robustscaler__quantile_range robustscaler__quantile_range: (25.0, 75.0)
20 @ robustscaler__with_centering robustscaler__with_centering: True
21 @ robustscaler__with_scaling robustscaler__with_scaling: True
22 @ xgbclassifier__base_score xgbclassifier__base_score: 0.5
23 @ xgbclassifier__booster xgbclassifier__booster: 'gbtree'
24 @ xgbclassifier__colsample_bylevel xgbclassifier__colsample_bylevel: 1
25 @ xgbclassifier__colsample_bytree xgbclassifier__colsample_bytree: 1
26 @ xgbclassifier__gamma xgbclassifier__gamma: 0
27 @ xgbclassifier__learning_rate xgbclassifier__learning_rate: 0.1
28 @ xgbclassifier__max_delta_step xgbclassifier__max_delta_step: 0
29 @ xgbclassifier__max_depth xgbclassifier__max_depth: 3
30 @ xgbclassifier__min_child_weight xgbclassifier__min_child_weight: 1
31 @ xgbclassifier__missing xgbclassifier__missing: nan
32 @ xgbclassifier__n_estimators xgbclassifier__n_estimators: 100
33 * xgbclassifier__n_jobs xgbclassifier__n_jobs: 1
34 * xgbclassifier__nthread xgbclassifier__nthread: None
35 @ xgbclassifier__objective xgbclassifier__objective: 'binary:logistic'
36 @ xgbclassifier__random_state xgbclassifier__random_state: 0
37 @ xgbclassifier__reg_alpha xgbclassifier__reg_alpha: 0
38 @ xgbclassifier__reg_lambda xgbclassifier__reg_lambda: 1
39 @ xgbclassifier__scale_pos_weight xgbclassifier__scale_pos_weight: 1
40 @ xgbclassifier__seed xgbclassifier__seed: None
41 @ xgbclassifier__silent xgbclassifier__silent: True
42 @ xgbclassifier__subsample xgbclassifier__subsample: 1
43 Note: @, searchable params in searchcv too.