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"In the snappily-titled Data Mining and Knowledge Discovery with Evolutionary Algorithms, leading researcher Alex A Freitas introduces both data mining and evolutionary algorithms. ... The aim is to introduce and address the key challenges to a high level of detail. With an understanding gleaned from this book, and source code available freely on the web, the world of data mining is your oyster." (Application Development Advisor, January/February, 2003)
Reseña del editor
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
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- EditorialSpringer
- Año de publicación2012
- ISBN 10 3642077633
- ISBN 13 9783642077630
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas280
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Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series)
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Data Mining and Knowledge Discovery With Evolutionary Algorithms
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Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9783642077630. Nº de ref. del artículo: 5556647
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Data Mining and Knowledge Discovery with Evolutionary Algorithms
Publicado por
Springer Berlin Heidelberg Mrz 2012, 2012
ISBN 10: 3642077633
ISBN 13: 9783642077630
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an area of active research. In general, data mining consists of extracting knowledge from data. In this book we particularly emphasize the importance of discovering comprehensible and interesting knowledge, which is potentially useful to the reader for intelligent decision making. In a nutshell, the motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions (rules or another form of knowledge representation). In contrast, most rule induction methods perform a local, greedy search in the space of candidate rules. Intuitively, the global search of evolutionary algorithms can discover interesting rules and patterns that would be missed by the greedy search. This book presents a comprehensive review of basic concepts on both data mining and evolutionary algorithms and discusses significant advances in the integration of these two areas. It is self-contained, explaining both basic concepts and advanced topics. This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics 280 pp. Englisch. Nº de ref. del artículo: 9783642077630
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Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series)
Librería: California Books, Miami, FL, Estados Unidos de America
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Condición: New. Nº de ref. del artículo: I-9783642077630
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Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Condición: New. In English. Nº de ref. del artículo: ria9783642077630_new
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Data Mining and Knowledge Discovery with Evolutionary Algorithms
Publicado por
Springer Berlin Heidelberg, 2012
ISBN 10: 3642077633
ISBN 13: 9783642077630
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses the integration of two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increas ingly popular in the last few years, and their integration is currently an area of active research. In essence, data mining consists of extracting valid, comprehensible, and in teresting knowledge from data. Data mining is actually an interdisciplinary field, since there are many kinds of methods that can be used to extract knowledge from data. Arguably, data mining mainly uses methods from machine learning (a branch of artificial intelligence) and statistics (including statistical pattern recog nition). Our discussion of data mining and evolutionary algorithms is primarily based on machine learning concepts and principles. In particular, in this book we emphasize the importance of discovering comprehensible, interesting knowledge, which the user can potentially use to make intelligent decisions. In a nutshell, the motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions (rules or another form of knowl edge representation). In contrast, most rule induction methods perform a local, greedy search in the space of candidate rules. Intuitively, the global search of evolutionary algorithms can discover interesting rules and patterns that would be missed by the greedy search. Nº de ref. del artículo: 9783642077630
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Data Mining and Knowledge Discovery with Evolutionary Algorithms
Publicado por
Springer Berlin Heidelberg, 2012
ISBN 10: 3642077633
ISBN 13: 9783642077630
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book integrates two areas of computer science, namely data mining and evolutionary algorithms (EAs). In essence, data mining consists of extracting interesting knowledge from data. The book presents a comprehensive review of both data mining and EAs an. Nº de ref. del artículo: 5046823
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Data Mining and Knowledge Discovery with Evolutionary Algorithms
Librería: Books Puddle, New York, NY, Estados Unidos de America
Calificación del vendedor: 4 de 5 estrellas
Condición: New. pp. 280. Nº de ref. del artículo: 262459006
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Data Mining and Knowledge Discovery With Evolutionary Algorithms
Librería: Revaluation Books, Exeter, Reino Unido
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Paperback. Condición: Brand New. reprint edition. 264 pages. 8.75x6.00x0.75 inches. In Stock. Nº de ref. del artículo: x-3642077633
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Data Mining and Knowledge Discovery with Evolutionary Algorithms
Impresión bajo demandaLibrería: Majestic Books, Hounslow, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Print on Demand pp. 280 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. Nº de ref. del artículo: 5388961
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