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vectors [3]. Whereas eigenvalues give the relative importance of these directions [3]. Finding the eigenvectors and eigenvalues of the covariance matrix is the equivalent of fitting those straight, principal-component lines to the variance of the data[1]. Source: [4] The eigenvector, v, and