MATLAB Answers

"ffnet" neural network crossvalidation

1 view (last 30 days)
laplace laplace
laplace laplace on 26 Jun 2013
Indices = crossvalind('Kfold',inputs , 10);
for i=1:10
test = (Indices == i);
train = ~test;
net = newff(inputs(:,train),targets(:,train),20,{},'trainscg');
[net,TR] = traingd(net,inputs,targets);
a = sim(net,inputs(:,train));
this is the code to apply crossvalidation feel free to use it:)
but there is a problem in crossvalind when your input set has a higher dimension than 1
in case your input set consists of row vectors then the crossvalind command should be modified as following:
[M, N] = size (inputs)
*so now my question is: in case my input set consists of column vectors how should i modify crossvalind to assign indices NOT to each element of every column vector *BUT to each column vector itself***
: in case someone wants to pass indices to the elements of column vectors of the "inputs matrix" he can do:
C = num2cell(inputs,1);%this will "break" the matrix(inputs) to column vectors
for i=1:length(inputs)
  1 Comment
Greg Heath
Greg Heath on 1 Jul 2013
I don't have crossvalind. However, I recall a post recommending cvpartition as a superior alternative. That reference also recommended crossval.
Hope this helps.

Sign in to comment.

Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!