logistic_regression.m

load ~/Downloads/q1x.dat
load ~/Downloads/q1y.dat

hold off
%scatter(q1x, q1y)
hold on

X = [ones(length(q1x), 1), q1x];
Y = q1y;

theta = zeros(size(X, 2), 1)
iterations = 20

for i = 1:iterations
  h = sigmoid(-1 * X * theta);
  grad = (Y - h)' * X;
  hessian = zeros(3, 3);

  for j = 1:length(X)
    feature_vec = X(j,:);
    h = sigmoid(-1 * feature_vec * theta);
    hessian = hessian - feature_vec' * feature_vec * (h) * (1-h);
  end
  
  theta = theta - inv(hessian) * grad'
end

hold on
positive = (Y == 1);
negative = (Y == 0);
x_vals = q1x(:,1);
y_vals = q1x(:,2);
scatter(x_vals(positive),y_vals(positive),100,'o');
scatter(x_vals(negative),y_vals(negative),100,'x');

dbx=[0:0.1:8];
dby=(-theta(1)-theta(2)*dbx)/theta(3);
plot(dbx,dby);