Mercurial > repos > bgruening > sklearn_feature_selection
view test-data/get_params12.tabular @ 24:4170e2bda73d draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d6333e7294e67be5968a41f404b66699cad4ae53"
author | bgruening |
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date | Thu, 07 Nov 2019 05:37:06 -0500 |
parents | ec25331946b8 |
children | 41b109e70a7f |
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Parameter Value * memory memory: None * steps "steps: [('rfe', RFE(estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=nan, n_estimators=100, n_jobs=1, nthread=None, objective='reg:linear', random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, silent=True, subsample=1), n_features_to_select=None, step=1, verbose=0))]" @ rfe "rfe: RFE(estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=nan, n_estimators=100, n_jobs=1, nthread=None, objective='reg:linear', random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, silent=True, subsample=1), n_features_to_select=None, step=1, verbose=0)" @ rfe__estimator__base_score rfe__estimator__base_score: 0.5 @ rfe__estimator__booster rfe__estimator__booster: 'gbtree' @ rfe__estimator__colsample_bylevel rfe__estimator__colsample_bylevel: 1 @ rfe__estimator__colsample_bytree rfe__estimator__colsample_bytree: 1 @ rfe__estimator__gamma rfe__estimator__gamma: 0 @ rfe__estimator__learning_rate rfe__estimator__learning_rate: 0.1 @ rfe__estimator__max_delta_step rfe__estimator__max_delta_step: 0 @ rfe__estimator__max_depth rfe__estimator__max_depth: 3 @ rfe__estimator__min_child_weight rfe__estimator__min_child_weight: 1 @ rfe__estimator__missing rfe__estimator__missing: nan @ rfe__estimator__n_estimators rfe__estimator__n_estimators: 100 * rfe__estimator__n_jobs rfe__estimator__n_jobs: 1 * rfe__estimator__nthread rfe__estimator__nthread: None @ rfe__estimator__objective rfe__estimator__objective: 'reg:linear' @ rfe__estimator__random_state rfe__estimator__random_state: 0 @ rfe__estimator__reg_alpha rfe__estimator__reg_alpha: 0 @ rfe__estimator__reg_lambda rfe__estimator__reg_lambda: 1 @ rfe__estimator__scale_pos_weight rfe__estimator__scale_pos_weight: 1 @ rfe__estimator__seed rfe__estimator__seed: None @ rfe__estimator__silent rfe__estimator__silent: True @ rfe__estimator__subsample rfe__estimator__subsample: 1 @ rfe__estimator "rfe__estimator: XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=nan, n_estimators=100, n_jobs=1, nthread=None, objective='reg:linear', random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, silent=True, subsample=1)" @ rfe__n_features_to_select rfe__n_features_to_select: None @ rfe__step rfe__step: 1 * rfe__verbose rfe__verbose: 0 Note: @, searchable params in searchcv too.