wehub-resource-sync
29 lines
764 B
Matlab
Executable File
29 lines
764 B
Matlab
Executable File
function [y, sigma, p] = knRegPred(model, Xt, t)
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% Prediction for Gaussian Process (kernel) regression model
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% Input:
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% model: trained model structure
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% Xt: d x n testing data
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% t (optional): 1 x n testing response
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% Output:
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% y: 1 x n prediction
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% sigma: variance
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% p: 1 x n likelihood of t
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% Written by Mo Chen (sth4nth@gmail.com).
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kn = model.kn;
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a = model.a;
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X = model.X;
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tbar = model.tbar;
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Kt = knCenter(kn,X,X,Xt);
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y = a'*Kt+tbar;
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%% probability prediction
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if nargout > 1
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alpha = model.alpha;
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beta = model.beta;
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U = model.U;
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XU = U'\Kt;
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sigma = sqrt(1/beta+(knCenter(kn,X,Xt)-dot(XU,XU,1))/alpha);
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end
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if nargin == 3 && nargout == 3
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p = exp(-0.5*(((t-y)./sigma).^2+log(2*pi))-log(sigma));
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end |