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Understanding Singular Vectors
David James and Cynthia Botteron
The College Mathematics Journal
Vol. 44, No. 3 (May 2013), pp. 220-226
Published by: Mathematical Association of America
Stable URL: http://www.jstor.org/stable/10.4169/college.math.j.44.3.220
Page Count: 7
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Summary A certain weighted average of the rows (and columns) of a non-negative matrix yields a surprisingly simple, heuristical approximation to its singular vectors. There are correspondingly good approximations to the singular values. Such rules of thumb provide an intuitive interpretation of the singular vectors that helps explain why the SVD is so effective in analyzing large data sets.
Copyright the Mathematical Association of America 2013