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Principal Components Analysis - CMU Statistics

Principal Components Analysis - CMU Statistics

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know that v is a covariance matrix, so it is symmetric, and then linear algebra tells us that the eigenvectors must be orthogonal to one another. Again because v is a covariance matrix, it is a positive matrix, in the sense that￿x ·v￿x ≥0 for any￿x. This …

  Covariance

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