comparison test-data/get_params12.tabular @ 0:000a3868885b draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty

0:000a3868885b

	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.