$1)$from sklearn.preprocessing import MinMaxScaler

$2)$normalization $=$ MinMaxScaler$()$

$3)$x$\_$scaled $=$ normalization.fit$($X$\_$train$)$

$4)$x$\_$train$\_$normalized $=$ x$\_$scaled.transform$($X$\_$train$)$

$5)$x$\_$test$\_$normalized $=$ x$\_$scaled.transform$($X$\_$test$)$

$6)$y$\_$scaled $=$ normalization.fit$($Y$\_$train.reshape$($len$($Y$\_$train$),1))$

$7)$y$\_$train$\_$normalized $=$ y$\_$scaled.transform$($Y$\_$train.reshape$($len$($Y$\_$train$),1)).$flatten$()$

$8)$y$\_$test$\_$normalized $=$ y$\_$scaled.transform$($Y$\_$test.reshape$($len$($Y$\_$test$),1)).$flatten$()$

Which of the following sentences is incorrect?

Group of answer choices

In line $6,$ we store the information about the scaling transformation on the label in the variable y$\_$scaled.

In line $4,$ we normalize the training set by subtracting its minimum value and dividing by the range length.

In line $3,$ we store the information about the scaling transformation on the feature in the variable x$\_$scaled.

In line $5,$ we normalize the test set by subtracting its minimum value and dividing by the range length.