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From: Dalmar on 4 Jun 2010 14:47
I have written this NN to classify different cases. Simulation is
excellent but I could not get the required target T during the
testing.
Please let me know your suggestion. I am desperate to solve this
problem due to submission of my postgraduate final year.
P: input data; T: targets, P2a: testing input data; t2: testing
targets
Regards
This is the Matlab code
Inline Attachment Follows: matrixdatatraining2.m

%% Neural Network Classification
% training Matrix data
load P0;load P1;load P2;load P3;load P4; % training data (Inputs)
size(Pi=909x3)
[r0 c0] = size(P0);
[r1 c1] = size(P1);
[r2 c2] = size(P2);
[r3 c3] = size(P3);
[r4 c4] = size(P4);

TARGET: t0=zeros(r0,1); t1=ones(r1,1)*-2;
t2=ones(r2,1)*2 ;t3=ones(r3,1)*-5;
t4=ones(r4,1)*5;

%% Taking Input training data
P=[P0; P1; P2; P3; P4];
T = [zeros(r0,1); ones(r1,1)*-2; ones(r2,1)*2 ;ones(r3,1)*-5;
ones(r4,1)*5]; %(Targets)


P = transpose(P);
T = transpose(T);


testing data
load P2a;%load P2a;load P3a;load P4a; % Testing data size(Pi=909x3)

[Pn,minp,maxp,Tn,mint,maxt]=premnmx(P,T);
[an,mina,maxa,sn,mins,maxs]=premnmx(P2a',t2');% normalization

%% Creating and training of the Neural Network
..


net = newff(minmax(Pn),[8,12,8,1],{'tansig','purelin','tansig',
'purelin'},'trainbr');%'trainbfg');%trainbr', trainlm);

net.trainParam.show = 100%inf;
net.trainParam.goal = 1e-5;
net.trainParam.lr = 0.01;
net.trainparam.lr_inc = 1.05;
net.trainparam.lr_dec = 0.7;
net.trainparam.max_perfect_inc = 1.04;
net.trainparam.mc = 0.9;
net.trainparam.min_grad = 1e-10;
net.trainParam.epochs = 500;

[net,tr] = train(net,Pn,Tn);
%% Save the Network

save matrixdatatraining, net;
%% simulatation
);

y = sim(net,an);
% un-ormalization

%[a1] = postmnmx(y,mins,maxs);

tt=postmnmx(y',mins,maxs);
% if you like plot the output
figure(1)
plot(tt,'r')
hold
%Current plot held
plot(t2)
title('Comparison between actual targets and predictions')

% [m,b,r] = postreg(a,T);

%% Plotting the training
%Here the network is simulated and its output plotted against
% the targets.
figure(2)

plot(s')
hold on
plot(T', 'r')
title('Comparison between actual targets and predictions')
hold off
xlabel('Epoches')

Any idea?
From: Greg Heath on 4 Jun 2010 17:53
On Jun 4, 2:47 pm, Dalmar <ybul...(a)googlemail.com> wrote:
> I have written this NN to classify different cases. Simulation is
> excellent but I could not get the required target T during the
> testing.
> Please let me know your suggestion. I am desperate to solve this
> problem due to submission of  my postgraduate final year.
> P: input data; T: targets, P2a: testing input data; t2: testing
> targets
> Regards
> This is the Matlab code
> Inline Attachment Follows: matrixdatatraining2.m
-----SNIP>
> Any idea?

Yes.

1. Please do not post separately to multiple groups.
2. Use a multiple group send list on a single post.

See my replies in comp.ai.neural-nets.

Any future correspondence should be sent to both
groups as I have done with this reply.

Hope this helps.

Greg

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