Mercurial > repos > bgruening > sklearn_model_validation

comparison test-data/get_params12.tabular @ 17:cf9aa11b91c8 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
author bgruening
date Wed, 15 May 2019 07:42:07 -0400
parents
children a5aed87b2cc0
comparison
equal deleted inserted replaced
16:86e1e2874460 17:cf9aa11b91c8
1 Parameter Value
2 * memory memory: None
3 * steps "steps: [('rfe', RFE(estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
4 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
5 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
6 n_jobs=1, nthread=None, objective='reg:linear', random_state=0,
7 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
8 silent=True, subsample=1),
9 n_features_to_select=None, step=1, verbose=0))]"
10 @ rfe "rfe: RFE(estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
11 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
12 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
13 n_jobs=1, nthread=None, objective='reg:linear', random_state=0,
14 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
15 silent=True, subsample=1),
16 n_features_to_select=None, step=1, verbose=0)"
17 @ rfe__estimator__base_score rfe__estimator__base_score: 0.5
18 @ rfe__estimator__booster rfe__estimator__booster: 'gbtree'
19 @ rfe__estimator__colsample_bylevel rfe__estimator__colsample_bylevel: 1
20 @ rfe__estimator__colsample_bytree rfe__estimator__colsample_bytree: 1
21 @ rfe__estimator__gamma rfe__estimator__gamma: 0
22 @ rfe__estimator__learning_rate rfe__estimator__learning_rate: 0.1
23 @ rfe__estimator__max_delta_step rfe__estimator__max_delta_step: 0
24 @ rfe__estimator__max_depth rfe__estimator__max_depth: 3
25 @ rfe__estimator__min_child_weight rfe__estimator__min_child_weight: 1
26 @ rfe__estimator__missing rfe__estimator__missing: nan
27 @ rfe__estimator__n_estimators rfe__estimator__n_estimators: 100
28 * rfe__estimator__n_jobs rfe__estimator__n_jobs: 1
29 * rfe__estimator__nthread rfe__estimator__nthread: None
30 @ rfe__estimator__objective rfe__estimator__objective: 'reg:linear'
31 @ rfe__estimator__random_state rfe__estimator__random_state: 0
32 @ rfe__estimator__reg_alpha rfe__estimator__reg_alpha: 0
33 @ rfe__estimator__reg_lambda rfe__estimator__reg_lambda: 1
34 @ rfe__estimator__scale_pos_weight rfe__estimator__scale_pos_weight: 1
35 @ rfe__estimator__seed rfe__estimator__seed: None
36 @ rfe__estimator__silent rfe__estimator__silent: True
37 @ rfe__estimator__subsample rfe__estimator__subsample: 1
38 @ rfe__estimator "rfe__estimator: XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
39 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
40 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
41 n_jobs=1, nthread=None, objective='reg:linear', random_state=0,
42 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
43 silent=True, subsample=1)"
44 @ rfe__n_features_to_select rfe__n_features_to_select: None
45 @ rfe__step rfe__step: 1
46 * rfe__verbose rfe__verbose: 0
47 Note: @, searchable params in searchcv too.