Description
Springer Nonlinear Dimensionality Reduction by John A. Lee, Michel Verleysen
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._x000D_ Table of contents : - _x000D_
High-Dimensional Data.- Characteristics of an Analysis Method.- Estimation of the Intrinsic Dimension.- Distance Preservation.- Topology Preservation.- Method comparisons.- Conclusions._x000D_