Question
In an abstract sense, the SVD or PCA can be thought of as a way to approximate a ***-dimensional matrix (i.e. a high number of ***) with a a few ***-dimensional matrices.
In an abstract sense, the SVD or PCA can be thought of as a way to approximate a high-dimensional matrix (i.e. a large number of columns) with a a few low-dimensional matrices.

Question
In an abstract sense, the SVD or PCA can be thought of as a way to approximate a ***-dimensional matrix (i.e. a high number of ***) with a a few ***-dimensional matrices.
?

Question
In an abstract sense, the SVD or PCA can be thought of as a way to approximate a ***-dimensional matrix (i.e. a high number of ***) with a a few ***-dimensional matrices.
In an abstract sense, the SVD or PCA can be thought of as a way to approximate a high-dimensional matrix (i.e. a large number of columns) with a a few low-dimensional matrices.
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owner: aelizzybeth - (no access) - Exploratory_Data_Analysis_with_R_Peng.pdf, p128

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