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Moving course1 to course1 subdir.

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Vahagn Khachatryan
2017-02-12 08:17:57 +00:00
parent f26649af32
commit 0f459c597c
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machine_learning/course1/mlclass-ex8-008/mlclass-ex8/multivariateGaussian.m Executable file
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function p = multivariateGaussian(X, mu, Sigma2)
%MULTIVARIATEGAUSSIAN Computes the probability density function of the
%multivariate gaussian distribution.
% p = MULTIVARIATEGAUSSIAN(X, mu, Sigma2) Computes the probability
% density function of the examples X under the multivariate gaussian
% distribution with parameters mu and Sigma2. If Sigma2 is a matrix, it is
% treated as the covariance matrix. If Sigma2 is a vector, it is treated
% as the \sigma^2 values of the variances in each dimension (a diagonal
% covariance matrix)
%
k = length(mu);
if (size(Sigma2, 2) == 1) || (size(Sigma2, 1) == 1)
Sigma2 = diag(Sigma2);
end
X = bsxfun(@minus, X, mu(:)');
p = (2 * pi) ^ (- k / 2) * det(Sigma2) ^ (-0.5) * ...
exp(-0.5 * sum(bsxfun(@times, X * pinv(Sigma2), X), 2));
end