Hello, I am studying LSTM Sequence to Sequence Time Series Regression for Indoor Environmental.
When I read MATLAB Documentation for "trainNetwork", I had a problem about array type
following is the MATLAB Documentation text
net = trainNetwork(sequences,Y,layers,options) trains a recurrent network (for example, an LSTM or GRU network) for the sequence data specified by sequences and responses specified by Y.
Sequence or time series data, specified as an N-by-1 cell array of numeric arrays, where N is the number of observations, or a numeric array representing a single sequence.
For cell array or numeric array input, the dimensions of the numeric arrays containing the sequences depend on the type of data.
N-by-1 cell array of numeric sequences, where N is the number of sequences. The sequences are matrices with R rows, where R is the number of responses. Each sequence must have the same number of time steps as the corresponding predictor sequence.
For sequence-to-sequence regression tasks with one observation, sequences can be a matrix. In this case, Y must be a matrix of responses.
The Problems are
- if my Input data(Array X) has multiple input variable(x1, x2, x3 ,... xn) for Single Response y, Must I change my X's Type to cell?
- I had tried MATLAB Example, but I didn't understand diffrences in 2 case(Mat to Mat, Cell to Cell)