[apbarraza]

This is my code in Octave (it is not correct but maybe you could help me find what is wrong):

function [N, theta, Eout] = trainLogisticRegression(eta, mfunc, bfunc, numPointsPerEpoch)
% Initialize some useful values
N=0;
theta = zeros(3, 1);
theta_last =  theta + 1;

while ((abs(theta-theta_last)>0.01)==1), %Iterate until convergence
	N = N +1;
	theta_last = theta;
	%Generate points for the epoch
	[X, y]  = getRandomPoints(numPointsPerEpoch, mfunc, bfunc);
	% Add intercept term
	X = [ones(numPointsPerEpoch, 1) X];
	%Gradient Descent
	for i = 1:numPointsPerEpoch
		e = y(i).*X(i, :)./(1+exp(y(i)*(theta'*X(i,:)')));
		%Adjusting parameters given gradient
		theta = theta + eta*e';
	end;
end

%New set of points to calculate the error
[X, y]  = getRandomPoints(numPointsPerEpoch, mfunc, bfunc);
% Add intercept term
X = [ones(numPointsPerEpoch, 1) X];

%Error measure
Eout = 1/numPointsPerEpoch*(sum(log( 1 + exp(-1*y.*(theta'*X')'))));

end

I run this 100 times and average N and Eout to get the requested answers.
Nonetheless, I´m missing something that I just can´t quite pin out.

Any help is appreciated.