MATLAB: Patternnet for multi-dimensional classification problem

Question

Hi,

I am trying to develop a neural network to model workplace choices of individuals. I have framed it as a classification problem where I give certain inputs (156 neurons) and I want it to classify my inputs into different zones and different industries at the same time. I have 151 zones and 11 industries to work with.

Given this set of input neurons, I want my target to receive a 1 corresponding to one of these 151 zones and 0 for others; and I want it to receive 1 corresponding to one of these 11 industries and 0 for others. However, patternnet does not seem to allow targets in this format.

Is there a way in which such a classification problem can be handled by a single neural net using patternnet? Can the targets be 3D or higher dimensional matrices (in the above case a 151 x 11 x no. of samples)?

I could always look at this as a classification problem with 151*11 classes, but I hate to increase the size of the neural net to such an extent.

In case, I cannot handle this using patternnet, what are other options for doing it? Can I use newff and apply hardlim to the network outputs (which will be 151 + 11, in this case)?

If you have any ideas, please answer at your earliest convenience. Any help appreciated!

Thanks in advance.

Answer 1

Use a 162 x N target matrix with two ones in every column.

If patternnet does not allow that, use feedforwardnet with 'trainscg'.

Use logsig instead of softmax in the output.

You can use vec2ind and ind2vec on target(1:11,:) and target(12:162,:)

Hope this helps.

Thank you for formally accepting my answer

Greg