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- Principle component analysis
Description
Principal component analysis (PCA) is a statistical procedure that uses orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.
Source:
OpenStax, Ear recognition. OpenStax CNX. Dec 18, 2013 Download for free at http://cnx.org/content/col11604/1.3
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