Mercurial > repos > bgruening > sklearn_generalized_linear
comparison test-data/get_params12.tabular @ 31:a8c7b9fa426c draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
| author | bgruening |
|---|---|
| date | Mon, 16 Dec 2019 05:29:33 -0500 |
| parents | b628de0d101f |
| children |
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| 30:67881a837f46 | 31:a8c7b9fa426c |
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| 1 Parameter Value | 1 Parameter Value |
| 2 * memory memory: None | 2 @ estimator "estimator: XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1, |
| 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, | 3 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, | 4 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100, |
| 41 n_jobs=1, nthread=None, objective='reg:linear', random_state=0, | 5 n_jobs=1, nthread=None, objective='reg:linear', random_state=0, |
| 42 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, | 6 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, |
| 43 silent=True, subsample=1)" | 7 silent=True, subsample=1)" |
| 44 @ rfe__n_features_to_select rfe__n_features_to_select: None | 8 @ n_features_to_select n_features_to_select: None |
| 45 @ rfe__step rfe__step: 1 | 9 * step step: 1 |
| 46 * rfe__verbose rfe__verbose: 0 | 10 * verbose verbose: 0 |
| 47 Note: @, searchable params in searchcv too. | 11 @ estimator__base_score estimator__base_score: 0.5 |
| 12 @ estimator__booster estimator__booster: 'gbtree' | |
| 13 @ estimator__colsample_bylevel estimator__colsample_bylevel: 1 | |
| 14 @ estimator__colsample_bytree estimator__colsample_bytree: 1 | |
| 15 @ estimator__gamma estimator__gamma: 0 | |
| 16 @ estimator__learning_rate estimator__learning_rate: 0.1 | |
| 17 @ estimator__max_delta_step estimator__max_delta_step: 0 | |
| 18 @ estimator__max_depth estimator__max_depth: 3 | |
| 19 @ estimator__min_child_weight estimator__min_child_weight: 1 | |
| 20 @ estimator__missing estimator__missing: nan | |
| 21 @ estimator__n_estimators estimator__n_estimators: 100 | |
| 22 * estimator__n_jobs estimator__n_jobs: 1 | |
| 23 * estimator__nthread estimator__nthread: None | |
| 24 @ estimator__objective estimator__objective: 'reg:linear' | |
| 25 @ estimator__random_state estimator__random_state: 0 | |
| 26 @ estimator__reg_alpha estimator__reg_alpha: 0 | |
| 27 @ estimator__reg_lambda estimator__reg_lambda: 1 | |
| 28 @ estimator__scale_pos_weight estimator__scale_pos_weight: 1 | |
| 29 @ estimator__seed estimator__seed: None | |
| 30 @ estimator__silent estimator__silent: True | |
| 31 @ estimator__subsample estimator__subsample: 1 | |
| 32 Note: @, params eligible for search in searchcv tool. |