Moving course1 to course1 subdir.

machine_learning/course1/mlclass-ex8-008/mlclass-ex8/visualizeFit.m

@@ -0,0 +1,20 @@
+function visualizeFit(X, mu, sigma2)
+%VISUALIZEFIT Visualize the dataset and its estimated distribution.
+%   VISUALIZEFIT(X, p, mu, sigma2) This visualization shows you the 
+%   probability density function of the Gaussian distribution. Each example
+%   has a location (x1, x2) that depends on its feature values.
+%
+
+[X1,X2] = meshgrid(0:.5:35); 
+Z = multivariateGaussian([X1(:) X2(:)],mu,sigma2);
+Z = reshape(Z,size(X1));
+
+plot(X(:, 1), X(:, 2),'bx');
+hold on;
+% Do not plot if there are infinities
+if (sum(isinf(Z)) == 0)
+    contour(X1, X2, Z, 10.^(-20:3:0)');
+end
+hold off;
+
+end