Classification and Clustering for Knowledge Discovery

Lipo Wang

ISBN 10: 3642065422 / ISBN 13: 9783642065422

Published by Springer Berlin Heidelberg, 2010

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783642065422

Bibliographic Details

• Title: Classification and Clustering for Knowledge Discovery
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2010
• Language: English
• ISBN 10: 3642065422
• ISBN 13: 9783642065422
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 20D millimeters 235 millimeters width by 155 millimeters height by 20 millimeters depth
• Weight: 557 grams

About this title

Synopsis

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.