Knowledge discovery from data streams /

Knowledge discovery from data streams /

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing dat...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Gama, João
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton, FL : Chapman & Hall/CRC, ©2010.
Colección:Chapman & Hall/CRC data mining and knowledge discovery series.
Temas:
Computer algorithms.
Machine learning.
Data mining.
Algorithms.
Artificial intelligence.
Algorithms
Artificial Intelligence
Data Mining
Algorithmes.
Apprentissage automatique.
Exploration de données (Informatique)
Intelligence artificielle.
algorithms.
artificial intelligence.
COMPUTERS > General.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |6 880-01  |a Knowledge discovery from data streams /  |c João Gama. 
260 |a Boca Raton, FL :  |b Chapman & Hall/CRC,  |c ©2010. 
300 |a 1 online resource (xix, 237 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Chapman & Hall/CRC data mining and knowledge discovery series 
588 0 |a Print version record. 
504 |a Includes bibliographical references and index. 
505 0 |a Front cover; Contents; List of Tables; List of Figures; List of Algorithms; Foreword; Acknowledgments; Chapter 1: Knowledge Discovery from Data Streams; Chapter 2: Introduction to Data Streams; Chapter 3: Change Detection; Chapter 4: Maintaining Histograms from Data Streams; Chapter 5: Evaluating Streaming Algorithms; Chapter 6: Clustering from Data Streams; Chapter 7: Frequent Pattern Mining; Chapter 8: Decision Trees from Data Streams; Chapter 9: Novelty Detection in Data Streams; Chapter 10: Ensembles of Classiers; Chapter 11: Time Series Data Streams; Chapter 12: Ubiquitous Data Mining. 
505 8 |a Chapter 13: Final CommentsAppendix A; Bibliography; Back cover. 
520 |a Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, 
542 |f Copyright © Chapman and Hall/CRC 2010  |g 2010 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Computer algorithms. 
650 0 |a Machine learning. 
650 0 |a Data mining. 
650 0 |a Algorithms. 
650 0 |a Artificial intelligence. 
650 2 |a Algorithms 
650 2 |a Artificial Intelligence 
650 2 |a Data Mining 
650 6 |a Algorithmes. 
650 6 |a Apprentissage automatique. 
650 6 |a Exploration de données (Informatique) 
650 6 |a Intelligence artificielle. 
650 7 |a algorithms.  |2 aat 
650 7 |a artificial intelligence.  |2 aat 
650 7 |a COMPUTERS  |x General.  |2 bisacsh 
650 7 |a Artificial intelligence.  |2 fast  |0 (OCoLC)fst00817247 
650 7 |a Algorithms.  |2 fast  |0 (OCoLC)fst00805020 
650 7 |a Computer algorithms.  |2 fast  |0 (OCoLC)fst00872010 
650 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
650 7 |a Machine learning.  |2 fast  |0 (OCoLC)fst01004795 
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