#NEWLINE# def _learning_curve( learning_curve ) : #NEWLINE# #INDENT# X = np . array ( ( [ [ 0 , 1 ] , [ 1 , 0 ] , [ 1 , 1 ] ] * 100 ) , dtype = float ) #NEWLINE# X [ : , 1 ] += ( np . random . random ( 300 ) - 0.5 ) #NEWLINE# y = np . array ( ( [ 0 , 0 , 1 ] * 100 ) ) #NEWLINE# dataset = Mock ( ) #NEWLINE# dataset . train_test_split . return_value = train_test_split ( X , y ) #NEWLINE# dataset . data = y #NEWLINE# dataset . target = y #NEWLINE# return learning_curve ( dataset , LogisticRegression ( ) , steps = 5 , verbose = 1 )