<p>From the reviews:</p>
<p></p>
<p>"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)</p>

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.
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This book addresses the integration of two areas of computer science, namely data mining and evolutionary algorithms.
Preface; 1. Introduction; 2. Data Mining Tasks and Concepts; 3. Data Mining Paradigms; 4. Data Prepration; 5. Basic Concepts of Evolutionary Algorithms; 6. Genetic Algorithms for Rule Discovery; 7. Genetic Programming for Rule Discovery and Decision-Tree Building; 8. Evolutionary Algorithms for Clustering; 9. Evolutionary Algorithms for Data Preparation; 10. Evolutionary Algorithms for Discovering Fuzzy Rules; 11. Scaling up Evolutionary Algorithms for Large Data Sets; 12. Conclusions and Research Directions; Index.
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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.
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Includes supplementary material: sn.pub/extras
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
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Produktdetaljer

ISBN
9783540433316
Publisert
2002-08-21
Utgiver
Vendor
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, UP, 06, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet

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