Mercurial > repos > bgruening > sklearn_fitted_model_eval
diff test-data/get_params12.tabular @ 0:eaddff553324 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
author | bgruening |
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date | Fri, 01 Nov 2019 17:15:22 -0400 |
parents | |
children | cf54bae8ad42 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/get_params12.tabular Fri Nov 01 17:15:22 2019 -0400 @@ -0,0 +1,47 @@ + 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.