32 lines
842 B
Mathematica
32 lines
842 B
Mathematica
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function [U, S] = pca(X)
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%PCA Run principal component analysis on the dataset X
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% [U, S, X] = pca(X) computes eigenvectors of the covariance matrix of X
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% Returns the eigenvectors U, the eigenvalues (on diagonal) in S
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%
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% Useful values
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[m, n] = size(X);
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% You need to return the following variables correctly.
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U = zeros(n);
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S = zeros(n);
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% ====================== YOUR CODE HERE ======================
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% Instructions: You should first compute the covariance matrix. Then, you
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% should use the "svd" function to compute the eigenvectors
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% and eigenvalues of the covariance matrix.
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%
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% Note: When computing the covariance matrix, remember to divide by m (the
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% number of examples).
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%
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% =========================================================================
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end
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