Transcription of A TUTORIAL ON PRINCIPAL COMPONENT ANALYSIS …
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A TUTORIAL ON PRINCIPAL COMPONENT ANALYSISD erivation, Discussion and Singular Value DecompositionJon March 2003|Version 1 PRINCIPAL COMPONENT ANALYSIS (PCA) is a mainstayof modern data ANALYSIS - a black box that is widelyused but poorly understood. The goal of this paper isto dispel the magic behind this black box. This tutorialfocuses on building a solid intuition for how and whyprincipal COMPONENT ANALYSIS works; furthermore, itcrystallizes this knowledge by deriving from first prin-cipals, the mathematics behind PCA . This tutorialdoes not shy away from explaining the ideas infor-mally, nor does it shy away from the hope is that by addressing both aspects, readersof all levels will be able to gain a better understand-ing of the power of PCA as well as the when, the howand the why of applying this COMPONENT ANALYSIS (PCA) has been calledone of the most valuable results from applied lin-ear used abundantly in all formsof ANALYSIS - from neuroscience to computer graphics.
ing of the power of PCA as well as the when, the how and the why of applying this technique. 1 Overview Principal component analysis (PCA) has been called one of the most valuable results from applied lin-ear algebra. PCA is used abundantly in all forms of analysis - from neuroscience to computer graphics - because it is a simple, non ...
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