Matrices as input and target for a neural network: "Number of inputs does not match net.numInputs."

I'm attempting to train a neural network with a 425x12273 uint8 matrix as the network input, and a 1x12273 uint8 matrix as the network target. I have 12273 training examples and correct outputs stored in these matrices (the first and second ones, respectively). The neural network I've created takes in 425 inputs and ultimately outputs a single value.

When attempting to run (where X is 425x12273, T is 1x12273)

 [net,tr] = train(net,X,T)

I get the error "Number of inputs does not match net.numInputs." How can I use these matrices as proper inputs to the network?

Note: I have tried

 X = num2cell(X, 1)
 T = num2cell(T, 1)

in order to get these matrices into cell array format; the error persists.

Answer 1

[MUHAMMED IRFAN]

Hello, Are you trying to attempt a classification problem ?? If so..

As I can understand , you are trying to train some 12273 elements , each of them are defined by their 425 features. You haven't mentioned in the question how many classes you want to classify them into .

You have just mentioned "correct outputs stored in these matrices (the first and second ones, respectively)". If you are trying to classify into 2 classes, your target should be og size 2 * 12273 instead of 1 * 12273 , each row corresponding to their respective classes.