Mercurial > repos > bgruening > sklearn_fitted_model_eval
diff test-data/get_params12.tabular @ 2:cf54bae8ad42 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author | bgruening |
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date | Mon, 16 Dec 2019 05:18:07 -0500 |
parents | eaddff553324 |
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--- a/test-data/get_params12.tabular Thu Nov 07 05:27:35 2019 -0500 +++ b/test-data/get_params12.tabular Mon Dec 16 05:18:07 2019 -0500 @@ -1,47 +1,32 @@ 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, +@ estimator "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. +@ n_features_to_select n_features_to_select: None +* step step: 1 +* verbose verbose: 0 +@ estimator__base_score estimator__base_score: 0.5 +@ estimator__booster estimator__booster: 'gbtree' +@ estimator__colsample_bylevel estimator__colsample_bylevel: 1 +@ estimator__colsample_bytree estimator__colsample_bytree: 1 +@ estimator__gamma estimator__gamma: 0 +@ estimator__learning_rate estimator__learning_rate: 0.1 +@ estimator__max_delta_step estimator__max_delta_step: 0 +@ estimator__max_depth estimator__max_depth: 3 +@ estimator__min_child_weight estimator__min_child_weight: 1 +@ estimator__missing estimator__missing: nan +@ estimator__n_estimators estimator__n_estimators: 100 +* estimator__n_jobs estimator__n_jobs: 1 +* estimator__nthread estimator__nthread: None +@ estimator__objective estimator__objective: 'reg:linear' +@ estimator__random_state estimator__random_state: 0 +@ estimator__reg_alpha estimator__reg_alpha: 0 +@ estimator__reg_lambda estimator__reg_lambda: 1 +@ estimator__scale_pos_weight estimator__scale_pos_weight: 1 +@ estimator__seed estimator__seed: None +@ estimator__silent estimator__silent: True +@ estimator__subsample estimator__subsample: 1 + Note: @, params eligible for search in searchcv tool.