![]() One category of statistical dimension reduction techniques is commonly called principal components analysis (PCA) or the singular value decomposition (SVD). Matrix data have some special statistical methods that can be applied to them. This is in contrast to a data frame, where every column of a data frame can potentially be of a different class. ![]() The key aspect of matrix data is that every element of the matrix is the same type and represents the same kind of measurement.
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