Suppose I have list like this:
dataset = [2,3,5,7,11,13]
# Split x_train where x_window is 3
x_train = [
[2,3,5],
[3,5,7],
]
# Split y_train where y_window is 2
y_train = [
[7,11],
[11,13],
]
Shall I normalize with Minimax scaling for entire dataset first before splitting train set? If so, then the min value for entire dataset is 2 while the max value for entire dataset is 13.
If no, shall I normalize the every x_train and every y_train? If so, then the min value is depends on value in element itself, for example x_train[0] min value is 2 while x_train[0] max value is 5.
I need to put it to the architecture of LSTM
model.add(LSTM(input=(x_train.shape[1],1))
model.add(Dense(y_train.shape[1]))