| 12345678910111213141516171819202122232425262728293031 |
- function [U, S] = pca(X)
- %PCA Run principal component analysis on the dataset X
- % [U, S, X] = pca(X) computes eigenvectors of the covariance matrix of X
- % Returns the eigenvectors U, the eigenvalues (on diagonal) in S
- %
- % Useful values
- [m, n] = size(X);
- % You need to return the following variables correctly.
- U = zeros(n);
- S = zeros(n);
- % ====================== YOUR CODE HERE ======================
- % Instructions: You should first compute the covariance matrix. Then, you
- % should use the "svd" function to compute the eigenvectors
- % and eigenvalues of the covariance matrix.
- %
- % Note: When computing the covariance matrix, remember to divide by m (the
- % number of examples).
- %
- sigma = 1 / m * X' * X;
- [U, S, V] = svd(sigma);
- % =========================================================================
- end
|
