Feature Engineering for Machine Learning by Alice Zheng and Amanda Casari

Author:Alice Zheng and Amanda Casari
Language: eng
Format: mobi, epub, pdf
Publisher: O'Reilly Media, Inc.
Published: 2018-04-09T16:00:00+00:00

Singular Value Decomposition (SVD) of a Matrix

Any rectangular matrix can be decomposed into three matrices of particular shapes and characteristics:

X = UΣVT

Here, U and V are orthogonal matrices (i.e., UTU = I and VTV = I). Σ is a diagonal matrix containing the singular values of X, which can be positive, zero, or negative. Suppose X has n rows and d columns and n ≥ d. Then U has shape n × d, and Σ and V have shape d × d. (See “Singular Value Decomposition (SVD)” for a full review of SVD and eigen decomposition of a matrix.)

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.