You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
25 lines
734 B
Matlab
25 lines
734 B
Matlab
10 years ago
|
function visualizeBoundary(X, y, model, varargin)
|
||
|
%VISUALIZEBOUNDARY plots a non-linear decision boundary learned by the SVM
|
||
|
% VISUALIZEBOUNDARYLINEAR(X, y, model) plots a non-linear decision
|
||
|
% boundary learned by the SVM and overlays the data on it
|
||
|
|
||
|
% Plot the training data on top of the boundary
|
||
|
plotData(X, y)
|
||
|
|
||
|
% Make classification predictions over a grid of values
|
||
|
x1plot = linspace(min(X(:,1)), max(X(:,1)), 100)';
|
||
|
x2plot = linspace(min(X(:,2)), max(X(:,2)), 100)';
|
||
|
[X1, X2] = meshgrid(x1plot, x2plot);
|
||
|
vals = zeros(size(X1));
|
||
|
for i = 1:size(X1, 2)
|
||
|
this_X = [X1(:, i), X2(:, i)];
|
||
|
vals(:, i) = svmPredict(model, this_X);
|
||
|
end
|
||
|
|
||
|
% Plot the SVM boundary
|
||
|
hold on
|
||
|
contour(X1, X2, vals, [0 0], 'Color', 'b');
|
||
|
hold off;
|
||
|
|
||
|
end
|