What are the application of defining the Classes in Neural Network ?
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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
2 Comments
Greg Heath
on 23 Feb 2015
What is this supposed to mean:
minmaxW0z = minmax(W0z); % [ 50 2 ]
minmaxW0zp = minmax(W0z'); % [ 61 2 ]
?
Accepted Answer
Greg Heath
on 24 Feb 2015
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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