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Quick Check 23.1 – Data 100, Summer 2020
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Which of these correspond to the definition of the first principal component? Suppose X is our centered data matrix, and we use the SVD on X to get U, Sigma, and V.
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The first column of Sigma @ V
The first column of U @ Sigma
The first column of X @ U
The first column of V
For which of the following reason(s) are the variables (i.e. the columns) of a data set centered prior to using PCA?
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You can only perform the SVD on centered matrices
Centering removes outliers from the data
Low rank approximations must go through the origin if we are using the SVD
None of the Above
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