# Do I have to scale/normalize my training data for LSTM Classification, even if I only have one feature?

I have a time-series data as follows:

# Time, Bitrate, Class
0.2,  312,     1
0.3,  319      1
0.5,  227      0
0.6,  229      0
0.7,  219      0
0.8,  341      1
1.0,  401      2


I am using only the "Bitrate" column as a feature, and "Class" for the labels for an LSTM classification model. In case of multiple features, I need to scale my data of course, to prevent domination from one feature to another. However, in my case, do I still need to scale/normalize my data, considering there is only one feature? Thanks!