Foundations of Computational Intelligence / Studies in Computational Intelligence Bd.206 (PDF)
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial...
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Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; artificial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are applied to Data Mining problems. Computational tools or solutions based on intelligent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated.
This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for Data Mining.
- 2009, 2009, 400 Seiten, Englisch
- Herausgegeben: Ajith Abraham, Aboul-Ella Hassanien, André Ponce de Leon F. de Carvalho, Vaclav Snásel
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3642010911
- ISBN-13: 9783642010910
- Erscheinungsdatum: 01.05.2009
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- Größe: 9.04 MB
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