BAYESIAN OPTIMIZATION OF A NEURAL NETWORK

I wrote the following code to optimize the architecture of a neural network via Bayesian optimization. What's wrong with it?

clc
clear
data = xlsread('Geor.xls')
t = data(:,5)'
x = data(:,1:4)'

trainFcn = 'trainbr'; 
hiddenLayerSize = optimizableVariable('hiddenLayerSize',[1,4]);

net.divideParam.trainRatio = optimizableVariable('net.divideParam.trainRatio',[0.4,0.75]);
vars =[hiddenLayerSize, net.divideParam.trainRatio]
net = fitnet(hiddenLayerSize,trainFcn);
net.divideParam.valRatio = 0.5*(100-net.divideParam.trainRatio*100)/100;
net.divideParam.testRatio =  0.5*(100-net.divideParam.trainRatio*100)/100;

[net,tr] = train(net,x,t);

y = net(x);
e = gsubtract(t,y);
mae = sum(abs(e))/40
performance = perform(net,t,y);

fun = @(x)mae(x, vars)
results = bayesopt(fun,vars)

[Peter Meglis]

Georgios,

"What's wrong with it?" Is an incredibly vague question. People here most likely aren't going to go through your code line by line and debug it for you. It will be beneficial to yourself and everyone else here if you add some details behind your question. It is better if you can have some specific questions that we can help answer.

Is there a certain error you are getting? Are the values you are getting unexpected? Is there a certain line of code that you have narrowed the problem down to?

Thanks

[Greg Heath]

If you want to use data to explain your problem, use a MATLAB set:

 help nndatasets
and
doc nndatasets

Greg

[Greg Heath]

 close all, clear all, clc

 x = [-1:.05:1];   % FROM HELP TRAINBR
 t = sin(2*pi*x)+0.1*randn(size(x));

 trainFcn = 'trainbr'; 
 hiddenLayerSize = optimizableVariable ('hiddenLayerSize',[1,4]);

 net.divideParam.trainRatio = optimizableVariable('net.divideParam.trainRatio',[0.4,0.75]);

 vars =[hiddenLayerSize,net.divideParam.trainRatio]
 net = fitnet(hiddenLayerSize,trainFcn);

 Error using fitnet (line 69)
 Parameters.hiddenSizes is not numeric.