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I have sensor dataset. I have already classified these data with LSTMs.I have a dataframe with 2 features and a class column. Assume that I take every two rows(inputs) respectively and make the dataframe as 4 features which means I merge two inputs together even they have same features.

Converting from Table 1

Time Feature 1 Feature 2 class
1 11 22 1
2 10 9 1
3 -5 -2 2
4 1 3 2

to Table 2

Time Feature 1 Feature 2 Feature 3 Feature 4 class
1 11 22 10 9 1
2 -5 -2 1 3 2

Is this configuration may increase accuracy? Is this configuration may lighten LSTMs? Maybe the provided data can be classificated with classical dense networks? Or, Is it not necessary?

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  • $\begingroup$ Waiting for answers.. $\endgroup$
    – dasmehdix
    Apr 14 at 8:56

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