So I'm not sure what word fits best to describe this data, probably "dimension" would be wrong since it may be used for flat samples with 3 features;
but by 3D data I mean some structure in a form of
[samples, timesteps, features]. And there are 2 features in each timestamp.
It looks like
[ [ [1,2], [3,4] ], [ [5,6], [7,8] ] ], like an LSTM input.
[1,2] is a timestep and
[[1,2],[3,4]] is a sample.
So one way is to just flatten out timesteps and make them into a 1D array. However is there any better way that would somehow utilize the information conducted by "grouping" of features inside a timestamp?
Also how do I properly describe this data structure?