From what I know, if the training set shape is [100, 500, 20], it represents 100 samples, each sample being 500 timeseries and each timeseries having 20 features. I'm wondering if I'm passing for example this shaped data, should each sample in order follow a temporal order?
For example, if the first sample start on 1/1/2000, and each timeseries is one day, that means that the first sample will end on 5/15/2001, the second sample starts on 5/16/2001, and so on.
Or could the different samples have different temporal order? For example the first sample starts on 1/1/2000, and ends on 5/15/2001, however the second sample could on 3/15/2002 and ends 500 days later on 7/28/2003 ?
Is this format correct or possible to pass into an RNN? Will the RNN produce good results if the samples are ordered like this?
If not, how should I shape my data so that the RNN will be able to effectively train on data like this?