Title

Exploring the Unknown Nature of Data: Cluster Analysis and Applications

Editor(s)

Olivas, Emilio Soria et. al.

Abstract

To classify objects based on their features and characteristics is one of the most important and primitive activities of human beings. The task becomes even more challenging when there is no ground truth available. Cluster analysis allows new opportunities in exploring the unknown nature of data through its aim to separate a finite data set, with little or no prior information, into a finite and discrete set of "natural," hidden data structures. Here, the authors introduce and discuss clustering algorithms that are related to machine learning and computational intelligence, particularly those based on neural networks. Neural networks are well known for their good learning capabilities, adaptation, ease of implementation, parallelization, speed, and flexibility, and they have demonstrated many successful applications in cluster analysis. The applications of cluster analysis in real world problems are also illustrated. Portions of the chapter are taken from Xu and Wunsch (2008).

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

9781605667669

Document Type

Book - Chapter

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2009 IGI Global, All rights reserved.


Share

 
COinS