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D1 · p. 12
PCA keeps the directions of greatest variance in the data, ordered by how much they explain.
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Think of each eigenvector as an axis the data stretches along. The bigger its eigenvalue, the more of the spread it captures D1 p. 12.
Quick check: why centre the data first?
Linear algebra
68% correct · weak: eigenvectors
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