I am using FITNET to try multiple DL functions on my data, which include 3840 training samples of 7 dim.
The output is 6 dimensions.
Using the following snipet and the data of the attached .mat file:
out_train = double(out_train');
in_train = double(in_train');
net = fitnet([56,28],'trainbr');
net = train(net, in_train, out_train);
I seem to get an mse approximation using Bayesian Regularization, of around 0.004 (my inputs/outputs are normalized on -1,1 but mostly centered close to 0 so thsi mse really affects the results).
The actuall prediction does not seem ok, having pretty high differences from the wanted values, even for the training set.
The correlation between my data is complex, and non-linear.
Using more layers, the iterations become extremely slow and eventually does not seem to help the problem much.
Any suggestion would be helpful.
Thanks in advance,