TY  - BOOK
AU  - Halgamuge,Saman
AU  - Wang,Lipo
ED  - SpringerLink (Online service)
TI  - Classification and Clustering for Knowledge Discovery
T2  - Studies in Computational Intelligence,
SN  - 9783540324041
AV  - TA329-348 
U1  - 519 23
PY  - 2005///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Engineering
KW  - Artificial intelligence
KW  - Computer vision
KW  - Computer aided design
KW  - Mathematics
KW  - Engineering mathematics
KW  - Appl.Mathematics/Computational Methods of Engineering
KW  - Artificial Intelligence (incl. Robotics)
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
KW  - Computer-Aided Engineering (CAD, CAE) and Design
KW  - Applications of Mathematics
KW  - Operations Research/Decision Theory
N2  - Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. "Classification and Clustering for Knowledge Discovery" also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications
UR  - http://dx.doi.org/10.1007/b98152
ER  -