MATLAB: What are the application of defining the Classes in Neural Network

classcodeneural networkneural networkstrueclass

Hi All
I was reading a comment in Neural Network to learn this topic more to develop my code
one thing I yet have not understood is that in the code we define classes in the code , what is that and why is it used ?
here is the comment :
%A quick way to see if any of the variables or classes appear to be different from the others is to standardize the inputs to zero-mean/unit-variance and compare the rows and columns of W0
%STANDARDIZATION (To compare Linear Model coefficients)
      zinputs = zscore(inputs')';
      W0z     = targets/[ones(1,N); zinputs];
      minmaxW0z  = minmax(W0z);   % [ 50 2 ]
      minmaxW0zp = minmax(W0z');  % [ 61 2 ]
      whos
      figure
      subplot(2,1,1)
      hold on
      plot(1:50,minmaxW0z(:,1),'bo')
      plot(1:50,minmaxW0z(:,2),'ro')
      subplot(2,1,2)
      hold on
      plot(1:61,minmaxW0zp(:,1),'bo')
      plot(1:61,minmaxW0zp(:,2),'ro')
%When the inputs are standardized, I see no significant differences between the weights associated with different classes or different variables

Best Answer

I don't think that you understand that MATLAB differentiates 4 basic types of nets
 Please read the command line documentation for
 help nndatasets
and
 doc nndatasets
 What type of data is simpleclass_dataset?
 How does it differ from simplefit_dataset?
 What type of net is fitnet?
 How does it differ from patternnet?
 Then read the online documentation at mathworks.com
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