Data Mining And Knowledge Discovery With Evolutionary Algorithms


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Data Mining and Knowledge Discovery with Evolutionary Algorithms


Data Mining and Knowledge Discovery with Evolutionary Algorithms

Author: Alex A. Freitas

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-11-11


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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.

Data Mining and Knowledge Discovery with Evolutionary Algorithms


Data Mining and Knowledge Discovery with Evolutionary Algorithms

Author: Alex A. Freitas

language: en

Publisher: Springer Science & Business Media

Release Date: 2002-08-21


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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 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

Data Mining And Knowledge Discovery With Evolutionary Algorithms


Data Mining And Knowledge Discovery With Evolutionary Algorithms

Author: Freitas Alex A.

language: en

Publisher:

Release Date: 2007-10-01


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