--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/get_params11.tabular	Wed May 15 07:42:07 2019 -0400
@@ -0,0 +1,46 @@
+	Parameter	Value
+*	memory	memory: None
+*	steps	"steps: [('editednearestneighbours', EditedNearestNeighbours(kind_sel='all', n_jobs=1, n_neighbors=3,
+            random_state=None, ratio=None, return_indices=False,
+            sampling_strategy='auto')), ('randomforestclassifier', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
+            max_depth=None, max_features='auto', max_leaf_nodes=None,
+            min_impurity_decrease=0.0, min_impurity_split=None,
+            min_samples_leaf=1, min_samples_split=2,
+            min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1,
+            oob_score=False, random_state=None, verbose=0,
+            warm_start=False))]"
+@	editednearestneighbours	"editednearestneighbours: EditedNearestNeighbours(kind_sel='all', n_jobs=1, n_neighbors=3,
+            random_state=None, ratio=None, return_indices=False,
+            sampling_strategy='auto')"
+@	randomforestclassifier	"randomforestclassifier: RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
+            max_depth=None, max_features='auto', max_leaf_nodes=None,
+            min_impurity_decrease=0.0, min_impurity_split=None,
+            min_samples_leaf=1, min_samples_split=2,
+            min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=1,
+            oob_score=False, random_state=None, verbose=0,
+            warm_start=False)"
+@	editednearestneighbours__kind_sel	editednearestneighbours__kind_sel: 'all'
+*	editednearestneighbours__n_jobs	editednearestneighbours__n_jobs: 1
+@	editednearestneighbours__n_neighbors	editednearestneighbours__n_neighbors: 3
+@	editednearestneighbours__random_state	editednearestneighbours__random_state: None
+@	editednearestneighbours__ratio	editednearestneighbours__ratio: None
+@	editednearestneighbours__return_indices	editednearestneighbours__return_indices: False
+@	editednearestneighbours__sampling_strategy	editednearestneighbours__sampling_strategy: 'auto'
+@	randomforestclassifier__bootstrap	randomforestclassifier__bootstrap: True
+@	randomforestclassifier__class_weight	randomforestclassifier__class_weight: None
+@	randomforestclassifier__criterion	randomforestclassifier__criterion: 'gini'
+@	randomforestclassifier__max_depth	randomforestclassifier__max_depth: None
+@	randomforestclassifier__max_features	randomforestclassifier__max_features: 'auto'
+@	randomforestclassifier__max_leaf_nodes	randomforestclassifier__max_leaf_nodes: None
+@	randomforestclassifier__min_impurity_decrease	randomforestclassifier__min_impurity_decrease: 0.0
+@	randomforestclassifier__min_impurity_split	randomforestclassifier__min_impurity_split: None
+@	randomforestclassifier__min_samples_leaf	randomforestclassifier__min_samples_leaf: 1
+@	randomforestclassifier__min_samples_split	randomforestclassifier__min_samples_split: 2
+@	randomforestclassifier__min_weight_fraction_leaf	randomforestclassifier__min_weight_fraction_leaf: 0.0
+@	randomforestclassifier__n_estimators	randomforestclassifier__n_estimators: 'warn'
+*	randomforestclassifier__n_jobs	randomforestclassifier__n_jobs: 1
+@	randomforestclassifier__oob_score	randomforestclassifier__oob_score: False
+@	randomforestclassifier__random_state	randomforestclassifier__random_state: None
+*	randomforestclassifier__verbose	randomforestclassifier__verbose: 0
+@	randomforestclassifier__warm_start	randomforestclassifier__warm_start: False
+	Note:	@, searchable params in searchcv too.