高斯过程分类绘制高斯曲面matlab代码

下面是一个简单的高斯过程分类绘制高斯曲面的Matlab代码示例：

% 生成数据
n = 50;
x1 = linspace(-5, 5, n)';
x2 = linspace(-5, 5, n)';
[X1, X2] = meshgrid(x1, x2);
X = [X1(:) X2(:)];
Y = peaks(X1, X2);

% 高斯过程分类
meanfunc = @meanConst;
hyp.mean = 0;
covfunc = @covSEard;
ell = 1;
sf = 1;
hyp.cov = log([ell ell sf]);
likfunc = @likGauss;
sn = 0.1;
hyp.lik = log(sn);
hyp = minimize(hyp, @gp, -100, @infGaussLik, meanfunc, covfunc, likfunc, X, Y);

% 预测
xs = linspace(-5, 5, 100)';
[xx, yy] = meshgrid(xs, xs);
xstar = [xx(:) yy(:)];
[mu, s2] = gp(hyp, @infGaussLik, meanfunc, covfunc, likfunc, X, Y, xstar);

% 绘制高斯曲面
figure;
surf(xx, yy, reshape(mu, length(xs), length(xs)))
hold on;
shading interp;
colormap(jet);
alpha(0.5);
plot3(X(:,1), X(:,2), Y, 'k.', 'MarkerSize', 20);
axis([-5 5 -5 5 -10 10]);
xlabel('x1');
ylabel('x2');
zlabel('y');

该代码生成一个高斯曲面，其中 `X` 和 `Y` 是用于训练高斯过程分类器的输入和输出数据，`xstar` 是要进行预测的点，`mu` 和 `s2` 是预测的平均值和方差，`surf` 函数用于绘制高斯曲面。