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Assume I have a m dimensional input feature vector and I would like to perform multiple steps time series forecasting. I have about 500 files which each one is has 100 observations for example consider following is file 1:

Current    Future 
    1 2 3     4 5 6

    4 5 6     7 8 9

    7 8 9     10 11 12

File 2 is like:

current            Future

1.2 1.4 1.6       2.5 2.7 2.9

2.5 2.7 2.9       3.5 3.7 3.9

3.5 3.7 3.9       4.5 4.7 4.9

How can I use these files for training?. I cannot concatenate files since orders matter in time series ? I also cannot sort them since they are multivariate not just one observation per time step. I can train one model per file but how can I take an advantage all these files and data?

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