gistfile1.matlab

clear all;
close all;
clc;

load data_logreg.mat;

isOctave = exist('OCTAVE_VERSION', 'builtin') ~= 0;

eta = 1;
options.degrees = [1 2 5 15];
options.methods = {'gd' 'gdad' 'builtin'};
options.iterations.gd = [10 100 1000];
options.iterations.gdad = [1000];
options.iterations.builtin = [1000];
options.fun.gd = @(eta, theta, iter) ...
  (@(cost_func) gradient_descent(cost_func, eta, theta, iter));
options.fun.gdad = @(eta, theta, iter) ...
  (@(cost_func) gradient_descent_adaptive(cost_func, eta, theta, iter));
if(isOctave)
  options.fun.builtin = @(eta, theta, iter) ...
    (@(cost_func) fminunc(cost_func, theta, ...
      optimset('GradObj', 'on', 'TolFun', 1e-8, 'TolX', 1e-8, 'MaxIter', iter)));
else
  options.fun.builtin = @(eta, theta, iter) ...
    (@(cost_func) fminunc(cost_func, theta, ...
      optimset('DerivativeCheck', 'off', ...
      'GradObj', 'on', 'TolFun', 1e-8, 'TolX', 1e-8, 'MaxIter', iter)));
end
options.formats = {'png'};

for meth = options.methods
  for deg = options.degrees
    for iter = options.iterations.(meth{1})

      [X_train, num_params] = ...
        logreg_poly_design_matrix(data.x1_train, data.x2_train, deg);
      theta = zeros(num_params,1);
      cost_func = @(theta) logreg_cost_function(theta, X_train, data.y_train);

      f = options.fun.(meth{1});
      g = f(eta, theta, iter);
      [theta, Jval] = g(cost_func);
      X_test = logreg_poly_design_matrix(data.x1_test, data.x2_test, deg);
      Jtest = logreg_cost_function(theta, X_test, data.y_test);

      fprintf('meth: %7s, deg: %2d, iter: %4d, Jval: %.5f, Jtest: %.5f\n', ...
              meth{1}, deg, iter, Jval, Jtest);
      if(isOctave)
        continue
      end
      h = figure('Visible','off','PaperUnits','inches','PaperPosition',[0 0 20 15]);
      logreg_plot(data, deg, theta, Jval, Jtest);
      for file = options.formats
        print(sprintf('-d%s', file{1}),'-r100', ...
              sprintf('plot-%s-%02d-%04d.%s', meth{1}, deg, iter, file{1}));
      end

    end
  end
end