how can i use genetic algorithm to teain preceptron

2011 3 21
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Timothy Felty
Timothy Felty 2011-3-21

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If you have a genetic algorithm already, the easiest way is to make the weights the chromosomes, and then use the error of the perceptron as the goal function. When error is less than your desired threshold freeze the best individual as the weights.
If you have different possible activation functions you could include them in the chromosomes and have the GA find that as well.

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mohammed
mohammed 2011-3-22
I have Perceptron algorthim,
could you help me to add GA for training
=================
inputs = xlsread('data1.xls', 1, 'A2:D115');
inputs=inputs';
targets = xlsread('data1.xls', 1, 'L2:L115');
targets = targets';
numHiddenNeurons = 20; % Adjust as desired
net = newpr(inputs,targets,numHiddenNeurons);
net.divideParam.trainRatio = 70/100; % Adjust as desired
net.divideParam.valRatio = 15/100; % Adjust as desired
net.divideParam.testRatio = 15/100; % Adjust as desired
net.trainParam.epochs= 1000;
net.trainParam.goal=0.01;
net.adaptFcn= 'trains';
% Train and Apply Network
net.trainFcn= 'trainbr';%'trainbfg''trainbr';'trainlm';
[net,tr] = train(net,inputs,targets);
outputs = sim(net,inputs);
=================

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mohammed
mohammed
2011-3-21

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