NeuralNET with Categorical Variables.
7 views (last 30 days)
I am trying to train a NN with a set number of Input variables, say "n", and a set of outputs say "m". I have two categories 1 and 2 . I have the data available for category 1 and category 2 both 1000 in number. both have the same number of Inputs/variables and same number of output/variables. Ofcourse depending on which category it belongs to, the outputs vary. I want to train them together that is I have 2 categories (1, and 2) and "n" input variables, generating "m" outputs. How do I set up the network (feed forward net is what I am using). I have done separately two networks for each and they work fine. but I want t train them together. Please help. Thanks in advance.
This is what I am currently using for single NN:
net = feedforwardnet(hiddenLayerSize);
net = configure(net, x, t);
[net,tr] = train(net,x,t);
Where hiddenLayerSize is number of nodes in hidden layer. Currently I have about 13 inputs 10 Hidden nodes and 9 outputs for each network.