Alex A. Freitas

Data Mining and Knowledge Discovery with Evolutionary Algorithms (eBook, PDF)

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 265
• Erscheinungstermin: 11. November 2013
• Englisch
• ISBN-13: 9783662049235
• Artikelnr.: 53381534

Autorenporträt

Alex A. Freitas, Pontificia Universidade Catolica do Parana, Curitiba, Brazil

Inhaltsangabe

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.

Rezensionen

From the reviews: "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)