Machine Learning, Logistics Regression, Logistic Regression Model, Logistic Regression, Regularization.
follows: function [J, grad] = computeCost(theta,x,y,lambda) [m,n] = size(x); x = [ones(m,1), x]; h = sigmoid(x * theta); % excluded the first theta value theta1 = [0 ; theta(2:size(theta), :)]; % reduce magnitude of the thetas p = lambda*(theta1'*theta1)/(2*m); J = ((-y)’*log(h) —