How to manually calculate a Neural Network output?
Dear experts, I am exploring the Neural Network Toolbox and would like to manually calculate output by hand. I used one of the example provided by Matlab with the following code. Unfortunately, my output is incorrect. Does anyone know why? Thanks %%below is the sample code from Matlab [x, y] = crab_dataset; size(x) % 6 x 200 size(y) % 2 x 200 setdemorandstream(491218382); net = patternnet(10); [net, tr_info] = train(net, x, y); testX = x(:, tr_info.testInd); testT = y(:, tr_info.testInd); testY = net(testX); testIndices = vec2ind(testY); [error_rate, conf_mat] = confusion(testT, testY); fprintf('Percentage Correct Classification : %f%%\n', 100*(1 - error_rate)); fprintf('Percentage Incorrect Classification : %f%%\n', 100*error_rate); %%Manually calculate the output by hand % nFeatures = 6 % nSamples = 200 % nHiddenNode = 10 % nClass = 2 % input layer => x (6x200) % hidden layer => h = sigmoid(w1.x + b1) % = (10x6)(6x200) + (10x1) % = (10x200) % % output layer => yhat = w2.h + b2 % = (2x200) w1 = net.IW{1}; % (10x6) w2 = net.LW{2}; % (2x10) b1 = net.b{1}; % (10x1) b2 = net.b{2}; % (2x1) h = sigmoid(w1*x + b1); yhat = w2*h + b2; [testY' yhat'] [vec2ind(testY)' vec2ind(yhat)']
Neeta Dsouza answered .
2025-11-20
[x, y] = crab_dataset;
size(x) % 6 x 200
size(y) % 2 x 200
setdemorandstream(491218382);
net = patternnet(10);
[net, tr_info] = train(net, x, y);
xoffset=net.inputs{1}.processSettings{1}.xoffset;
gain=net.inputs{1}.processSettings{1}.gain;
ymin=net.inputs{1}.processSettings{1}.ymin;
w1 = net.IW{1}; % (10x6)
w2 = net.LW{2}; % (2x10)
b1 = net.b{1}; % (10x1)
b2 = net.b{2};
% Input 1
y1 = bsxfun(@times,bsxfun(@minus,x,xoffset),gain);
y1 = bsxfun(@plus,y1,ymin);
% Layer 1
a1 = 2 ./ (1 + exp(-2*(repmat(b1,1,size(x,2)) + w1*y1))) - 1;
% output
n=repmat(b2,1,size(x,2)) + w2*a1;
nmax = max(n,[],1);
n = bsxfun(@minus,n,nmax);
num = exp(n);
den = sum(num,1);
den(den == 0) = 1;
y2 = bsxfun(@rdivide,num,den);%y2==outputnet == net(x)