Hello everyone, I am trying to use an LSTM to predict and forecast the position of a vehicle and I would like to know how to train the system.
I have a dataset consisting of 230 vehicle samples i.e. a cell of 1 x 230 where each sample is a matrix of 4 features and the respective sequence length(60 - 300 timesteps). The objective is to forecast future (1 - 5 timesteps) steps of a given vehicle sample.
I am refering to this example to understand the way to forecast and this to see how to train the model for prediction. But in both the examples the LSTM model is used as a many to one example.
my features are in the x,y coordinate..
I would like to know how to train a LSTM model on multiple sequences containing mutltiple features and learn the behaviour of the vehicle model!
Thanks in advance