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Nonlinear Dimensionality Reduction (Information Science and Statistics)

By: John A. Lee (Author) , Michel Verleysen (Author)

Extended Catalogue

Ksh 27,350.00

Format: Paperback or Softback

ISBN-10: 1441922881

ISBN-13: 9781441922885

Collection / Series: Information Science and Statistics

Collection Type: Publisher collection

Edition statement: 1st ed. Softcover of orig. ed. 2007

Publisher: Springer-Verlag New York Inc.

Imprint: Springer-Verlag New York Inc.

Country of Manufacture: US

Country of Publication: GB

Publication Date: Nov 19th, 2010

Publication Status: Active

Product extent: 309 Pages

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However, since the late nineties, many new methods have been developed and nonlinear dimensionality reduction, also called manifold learning, has become a hot topic. The purpose of the book is to summarize clear facts and ideas about well-known methods as well as recent developments in the topic of nonlinear dimensionality reduction.

This book describes established and advanced methods for reducing the dimensionality of numerical databases. Each description starts from intuitive ideas, develops the necessary mathematical details, and ends by outlining the algorithmic implementation. The text provides a lucid summary of facts and concepts relating to well-known methods as well as recent developments in nonlinear dimensionality reduction. Methods are all described from a unifying point of view, which helps to highlight their respective strengths and shortcomings. The presentation will appeal to statisticians, computer scientists and data analysts, and other practitioners having a basic background in statistics or computational learning.


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