Transcription of A Tutorial on Principal Component Analysis
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A Tutorial on Principal Component Analysis
A Tutorial on Principal Component AnalysisJonathon Shlens Systems Neurobiology Laboratory,Salk Insitute for Biological StudiesLa Jolla, CA 92037 andInstitute for Nonlinear Science,University of California,San DiegoLa Jolla, CA 92093-0402(Dated: December 10, 2005; Version 2) Principal Component Analysis (PCA) is a mainstay of modern data Analysis - a black box thatis widely used but poorly understood. The goal of this paper is to dispel the magic behind thisblack box. This Tutorial focuses on building a solid intuition for how and why Principal componentanalysis works; furthermore, it crystallizes this knowledge by deriving from simple intuitions, themathematics behindPCA. This Tutorial does not shy away from explaining the ideas informally,nor does it shy away from the mathematics.
black box. This tutorial focuses on building a solid intuition for how and why principal component analysis works; furthermore, it crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA . This tutorial does not shy away from explaining the ideas informally, nor does it shy away from the mathematics.
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