Help for mathematical equation of regression in ANN

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b
b 2012-5-15
With ANN toolbox, I am using neural networks for finding the regression equation.
for info, I am using Bayesian regularization with 4 variables of 30 different samples and 30 results.
Is there a way of finding the mathematical equation of that in ANN?
Thanks..

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采纳的回答

Greg Heath
Greg Heath 2012-5-16
This question has been asked many times in both the Newsgroup and Answers. If you do not use the default normalizations of input and output,
h = tansig(IW*x+b1);
y = purelin(LW*h+b2);
Otherwise you have to use the default mapminmax or alternative mapstd on x,t and y.
You can obtain details by searching on the equation for h in the Newgroup and Answers.
Hope this helps.
Greg

更多回答（4 个）

b
b 2012-5-16
Thank you so much but,
inputs = initial1';
targets = output';
hiddenLayerSize = 30;
net = newff(minmax(input),[1 10],{'tansig' 'purelin'},'trainbr');
net.IW{1}
net.b{1,1}
h=tansig(IW*inputs+b1)
targets=purelin(LW*h+b2)
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 80/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 5/100;
net.trainFcn = 'trainbr'; % Bayesian Regularization
net.performFcn = 'mse'; % Mean squared error
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotregression', 'plotfit'};
[net,tr] = train(net,inputs,targets);
outputs = net(inputs);
errors = gsubtract(targets,outputs);
performance = perform(net,targets,outputs)
trainTargets = targets .* tr.trainMask{1};
valTargets = targets .* tr.valMask{1};
testTargets = targets .* tr.testMask{1};
trainPerformance = perform(net,trainTargets,outputs)
valPerformance = perform(net,valTargets,outputs)
testPerformance = perform(net,testTargets,outputs)
view(net)
perf = msereg(errors,outputs,X,FP);
dy = msereg('dy',errors,outputs,X,perf,FP);
dx = msereg('dx',errors,outputs,X,perf,FP);
info = msereg(code);
net.performParam.ratio = 20/(20+1);
perf = msereg(e,net);
Gives an error why??
  2 个评论
Greg Heath
Greg Heath 2012-5-16
What is the error?
Did you try to use the debugger?
Greg
b
b 2012-5-17
I am using debugger, but actually,
net.IW{1}
net.b{1,1}
There is an error. I could not solve it.

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Greg Heath
Greg Heath 2012-5-16
hiddenLayerSize = 30;
1. TOO LARGE AND INCOMPATIBLE WITH NEXT COMMAND
net = newff(minmax(input),[1 10],{'tansig' 'purelin'},'trainbr');
2. a. OBSOLETE. WHAT VERSION OF MATAB AND NNTBX DO YOU HAVE?
2.b. INCORRECT NODE SIZE ASSIGNNMENT SYNTAX
net.IW{1}
net.b{1,1}
3. ASSIGN WEIGHTS TO IW, LW
h=tansig(IW*inputs+b1)
targets=purelin(LW*h+b2)
4. TERMINATE THIS AND OTHER VOLUMINOUS OUTPUT COMMANDS WITH SEMICOLONS
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
4. LAST FOUR ARE DEFAULTS: DELETE
net.divideParam.valRatio = 15/100;
5. WHY ARE YOU USING A VALIDATION SET WITH TRAINBR?
net.trainFcn = 'trainbr'; % Bayesian Regularization
6. WHY ARE YOU USING TRAINBR INSTEAD OF DEFAULT TRAINLM?
net.performFcn = 'mse'; % Mean squared error
7. MSE INCOMPATIBLE WITH TRAINBR SEE DOCUMENTATION
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotregression', 'plotfit'};
8. NOT SURE IF THESE ARE COMPATIBLE WITH YOUR OBSOLETE VERSION OF NEWFF
perf = msereg(errors,outputs,X,FP);
dy = msereg('dy',errors,outputs,X,perf,FP);
dx = msereg('dx',errors,outputs,X,perf,FP);
info = msereg(code);
net.performParam.ratio = 20/(20+1);
perf = msereg(e,net);
9. I HAVE NO IDEA WHAT YOU ARE DOING HERE. YOU NEVER USED MSEREG FOR LEARNING
HOPE THIS HELPS.
GREG
b
b 2012-5-17
hiddenLayerSize=10;
# 1- HIDDENLAYERSIZE 30 CHANGED TO 10.
# 2- MATLAB 2012a.(FORGOT TO ADD IT, SORRY FOR THAT)
net.IW{1}
net.b{1,1}
# 3- WHEN I WROTE getwb(net), IW AND B OCCUR LIKE THAT.
h=tansig(IW*inputs+b1);
targets=purelin(LW*h+b2);
# 4- SEMICOLONS ARE ADDED.
net.trainFcn='trainlm'
# 5- IT IS CHANGED TO 'TRAINLM'. IN MANY ARTICLES, BAYESIAN IS WORKED FOR MEDIA OPTIMIZATION. I CAN USE 'LM' IN MY PROJECT
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotregression', 'plotfit'};
# 6- THEY ARE COMPATIBLE AND WORKING WITHOUT AN ERROR.
dy = msereg('dy',errors,outputs,X,perf,FP);
dx = msereg('dx',errors,outputs,X,perf,FP);
info = msereg(code);
net.performParam.ratio = 20/(20+1);
perf = msereg(e,net);
# 7- THESE FOR OBTAINIG MSEREG AND PERFORMANCE.
CAN I USE 'ADAPT' MSEREG FOR LEARNING.
THANK YOU SO MUCH.
BASAR
  2 个评论
b
b 2012-5-17
The last sentence is not correct.
I misunderstood what you said in your last sentence.

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b
b 2012-5-17
Also, in one of your previous answers, you told to use.
help msereg
in the help part, it is explained like that
perf = msereg(errors,outputs,X,FP);
dy = msereg('dy',errors,outputs,X,perf,FP);
dx = msereg('dx',errors,outputs,X,perf,FP);
info = msereg(code);
net.performParam.ratio = 20/(20+1);
perf = msereg(e,net);

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