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 INDICE: 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 forLarge Data Sets; 12. Conclusions and Research Directions; Index.
- ISBN: 978-3-642-07763-0
- Editorial: Springer
- Encuadernacion: Rústica
- Fecha Publicación: 31/03/2012
- Nº Volúmenes: 1
- Idioma: Inglés