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Geometric Structure Of Highdimensional Data And Dimensionality Reduction 1st Edition Prof Jianzhong Wang Auth

  • SKU: BELL-4240862
Geometric Structure Of Highdimensional Data And Dimensionality Reduction 1st Edition Prof Jianzhong Wang Auth
$ 31.00 $ 45.00 (-31%)

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Geometric Structure Of Highdimensional Data And Dimensionality Reduction 1st Edition Prof Jianzhong Wang Auth instant download after payment.

Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 7.75 MB
Pages: 356
Author: Prof. Jianzhong Wang (auth.)
ISBN: 9783642274961, 9783642274978, 364227496X, 3642274978
Language: English
Year: 2011
Edition: 1

Product desciption

Geometric Structure Of Highdimensional Data And Dimensionality Reduction 1st Edition Prof Jianzhong Wang Auth by Prof. Jianzhong Wang (auth.) 9783642274961, 9783642274978, 364227496X, 3642274978 instant download after payment.

"Geometric Structure of High-Dimensional Data and Dimensionality Reduction" adopts data geometry as a framework to address various methods of dimensionality reduction. In addition to the introduction to well-known linear methods, the book moreover stresses the recently developed nonlinear methods and introduces the applications of dimensionality reduction in many areas, such as face recognition, image segmentation, data classification, data visualization, and hyperspectral imagery data analysis. Numerous tables and graphs are included to illustrate the ideas, effects, and shortcomings of the methods. MATLAB code of all dimensionality reduction algorithms is provided to aid the readers with the implementations on computers.

The book will be useful for mathematicians, statisticians, computer scientists, and data analysts. It is also a valuable handbook for other practitioners who have a basic background in mathematics, statistics and/or computer algorithms, like internet search engine designers, physicists, geologists, electronic engineers, and economists.

Jianzhong Wang is a Professor of Mathematics at Sam Houston State University, U.S.A.

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