Reputation: 5982
I´m trying to train a neural network using nprtool and also manually, calling newpr and train methods. I use samples oriented as rows, instead of default as columns:
Using nprtool there is no problem, but when I call to the automatically generated M-file, the output is:
??? Error using ==> network.train at 145
Targets are incorrectly sized for network.
Matrix must have 24 columns.
Error in ==> create_pr_net at 29
[net,tr] = train(net,inputs,targets);
My inputs are 140x24, and my targets are 140x3.
The generated code by Matlab is:
function net = create_pr_net(inputs,targets)
%CREATE_PR_NET Creates and trains a pattern recognition neural network.
%
% NET = CREATE_PR_NET(INPUTS,TARGETS) takes these arguments:
% INPUTS - RxQ matrix of Q R-element input samples
% TARGETS - SxQ matrix of Q S-element associated target samples, where
% each column contains a single 1, with all other elements set to 0.
% and returns these results:
% NET - The trained neural network
%
% For example, to solve the Iris dataset problem with this function:
%
% load iris_dataset
% net = create_pr_net(irisInputs,irisTargets);
% irisOutputs = sim(net,irisInputs);
%
% To reproduce the results you obtained in NPRTOOL:
%
% net = create_pr_net(inputs,targets);
% Create Network
numHiddenNeurons = 2000; % Adjust as desired
net = newpr(inputs,targets,numHiddenNeurons);
net.divideParam.trainRatio = 90/100; % Adjust as desired
net.divideParam.valRatio = 5/100; % Adjust as desired
net.divideParam.testRatio = 5/100; % Adjust as desired
% Train and Apply Network
[net,tr] = train(net,inputs,targets);
outputs = sim(net,inputs);
% Plot
plotperf(tr)
plotconfusion(targets,outputs)
I am using Matlab R2010a.
Thanks.
Upvotes: 0
Views: 3226
Reputation: 824
As mentioned in Matlab help file:
INPUTS - RxQ matrix of Q R-element input samples TARGETS - SxQ matrix of Q S-element associated target samples
You probably need a transpose of input and target matrix, before calling the Matlab train function manually.
Input = Input';
and
Taget = Target';
Upvotes: 3