[regression] updated exercise infrastructure

regression/code/checkdescent.m

@@ -1,25 +0,0 @@
-% data:
-load('lin_regression.mat')
-
-% compute mean squared error for a range of slopes and intercepts:
-slopes = -5:0.25:5;
-intercepts = -30:1:30;
-errors = zeros(length(slopes), length(intercepts));
-for i = 1:length(slopes)
-    for j = 1:length(intercepts)
-	      errors(i,j) = lsqError([slopes(i), intercepts(j)], x, y);
-    end
-end
-
-% minimum of error surface:
-[me, mi] = min(errors(:));
-[ia, ib] = ind2sub(size(errors), mi);
-eparams = [errors(ia), errors(ib)];
-
-% gradient descent:
-pstart = [-2. 10.];
-[params, errors] = descent(x, y, pstart);
-
-% comparison:
-fprintf('descent: %6.3f  %6.3f\n', params(1), params(2));
-fprintf('errors:  %6.3f  %6.3f\n', eparams(1), eparams(2));

regression/code/descent.m

@@ -1,15 +0,0 @@
-function [params, errors] = descent(xdata, ydata, pstart)
-    mingradient = 0.1;
-    eps = 0.01;
-    
-    errors = [];
-    params = pstart;
-    count = 1;
-    gradient = [100.0, 100.0];
-    while norm(gradient) > mingradient
-        gradient = lsqGradient(params, xdata, ydata);
-        errors(count) = lsqError(params, xdata, ydata);
-        params = params - eps .* gradient; 
-        count = count + 1;
-    end
-end

regression/code/descentfit.m

@@ -1,22 +0,0 @@
-clear 
-close all
-load('lin_regression.mat')
-
-pstart = [-2. 10.];
-[params, errors] = descent(x, y, pstart);
-
-figure()
-subplot(2,1,1)
-hold on
-scatter(x, y, 'displayname', 'data')
-xx = min(x):0.01:max(x);
-fx = params(1)*xx + params(2);
-plot(xx, fx, 'displayname', 'fit')
-xlabel('Input')
-ylabel('Output')
-grid on
-legend show
-subplot(2,1,2)
-plot(errors)
-xlabel('optimization steps')
-ylabel('error')

regression/code/linefit.m

@@ -1,18 +0,0 @@
-% data:
-load('lin_regression.mat')
-
-% gradient descent:
-pstart = [-2. 10.];
-[params, errors] = descent(x, y, pstart);
-
-% lsqcurvefit:
-line = @(p, x)  x.* p(1) + p(2);
-cparams = lsqcurvefit(line, pstart, x, y);
-
-% polyfit:
-pparams = polyfit(x, y, 1);
-
-% comparison:
-fprintf('descent:     %6.3f  %6.3f\n', params(1), params(2));
-fprintf('lsqcurvefit: %6.3f  %6.3f\n', cparams(1), cparams(2));
-fprintf('polyfit:     %6.3f  %6.3f\n', pparams(1), pparams(2));