@@ -493,10 +493,12 @@ def test_X_as_list():
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cv = KFold (n_splits = 3 )
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for scoring in (None , 'accuracy' , ('accuracy' , ),
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- ('accuracy' , 'precision ' )):
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+ ('accuracy' , 'recall ' )):
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grid_search = GridSearchCV (clf , {'foo_param' : [1 , 2 , 3 ]}, cv = cv ,
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- scoring = scoring )
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- grid_search .fit (X .tolist (), y ).score (X , y )
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+ scoring = scoring ,
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+ refit = 'accuracy'
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+ if scoring and len (scoring ) > 0 else True )
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+ grid_search .fit (X .tolist (), y ).score (X .tolist (), y )
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assert_true (hasattr (grid_search , "cv_results_" ))
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@@ -509,10 +511,12 @@ def test_y_as_list():
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cv = KFold (n_splits = 3 )
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for scoring in (None , 'accuracy' , ('accuracy' , ),
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- ('accuracy' , 'precision ' )):
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+ ('accuracy' , 'recall ' )):
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grid_search = GridSearchCV (clf , {'foo_param' : [1 , 2 , 3 ]}, cv = cv ,
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- scoring = scoring )
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- grid_search .fit (X , y .tolist ()).score (X , y )
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+ scoring = scoring ,
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+ refit = 'accuracy'
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+ if scoring and len (scoring ) > 0 else True )
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+ grid_search .fit (X , y .tolist ()).score (X , y .tolist ())
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assert_true (hasattr (grid_search , "cv_results_" ))
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