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OverviewHigh Quality Content by WIKIPEDIA articles! In geometric data analysis and statistical shape analysis, principal geodesic analysis is a generalization of principal component analysis to a non-Euclidean, non-linear setting of manifolds suitable for use with shape descriptors such as medial representations. Principal component analysis (PCA) involves a mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. Depending on the field of application, it is also named the discrete Karhunen-Loeve transform (K.L.T.), the Hotelling transform or proper orthogonal decomposition (POD). Full Product DetailsAuthor: Lambert M. Surhone , Mariam T. Tennoe , Susan F. HenssonowPublisher: VDM Publishing House Imprint: VDM Publishing House Dimensions: Width: 22.90cm , Height: 0.50cm , Length: 15.20cm Weight: 0.151kg ISBN: 9786131245305ISBN 10: 6131245304 Pages: 94 Publication Date: 14 August 2010 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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