Mercurial > repos > bgruening > scipy_sparse

diff test-data/get_params12.tabular @ 31:a2da4cebc584 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author bgruening
date Mon, 16 Dec 2019 05:43:45 -0500
parents b9ed7b774ba3
children
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--- a/test-data/get_params12.tabular	Thu Nov 07 05:45:58 2019 -0500
+++ b/test-data/get_params12.tabular	Mon Dec 16 05:43:45 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.