Derive PCA from Gaussian Ellipse
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Principle component analysis (PCA) is a fundamental tool for dimension reduction. It’s operations is quite simple: center the data, calculate the covariance matrix, perform eigenvalue decomposition and these eigenvector are “principle components”, which is also called eigenface if the data is face images.