Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams: v. 207 - Rilegato

Bifet, Albert

Rilegato

ISBN 10: 1607500906 ISBN 13: 9781607500902

Casa editrice: Ios Pr Inc, 2010

Riassunto

This book focuses on the design of learning algorithms for evolving and time-changing data streams, specifically the adaptive sliding window algorithm (ADWIN) for change detection and value estimation and its use in predictive learning, clustering, and closed frequent tree mining from time-changing data streams. The first section introduces a framework for developing algorithms that can learn from data streams that change over time. It presents an ADWIN for detecting change and keeping statistics from a data stream updated. The second part of the book describes connected acyclic graphs, or 'trees,' from the point of view of closure-based mining, presenting efficient algorithms for subtree testing and for mining ordered and unordered frequent closed trees. The third section presents high-performance algorithms for mining rooted trees adaptively from data streams that change over time. There is also a general methodology presented for identifying closed patterns in a data stream, with examples of three different types. Bifet teaches computer science at the University of Waikato, New Zealand. Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)

Dettagli dell'edizione

• Editore: Ios Pr Inc
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 1607500906
• ISBN 13: 9781607500902
• Rilegatura: Copertina rigida
• Numero di pagine: 212
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile