TY  - BOOK
AU  - Wang,Jianzhong
ED  - SpringerLink (Online service)
TI  - Geometric Structure of High-Dimensional Data and Dimensionality Reduction
SN  - 9783642274978
AV  - QA76.9.D343 
U1  - 006.312 23
PY  - 2011///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Data structures (Computer science)
KW  - Data mining
KW  - Mathematics
KW  - Computer Science
KW  - Data Mining and Knowledge Discovery
KW  - Probability and Statistics in Computer Science
KW  - Applications of Mathematics
KW  - Data Structures, Cryptology and Information Theory
N2  - "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
UR  - http://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-27497-8
ER  -