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Automating the Design of Data Mining Algorithms : An Evolutionary Computation Approach / by Gisele L. Pappa, Alex Freitas
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Natural Computing Series | SpringerLink BücherPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Description: Online-Ressource (XIII, 187p, digital)ISBN:- 9783642025419
- 006.312
- QA76.9.D343
Contents:
Summary: Traditionally, evolutionary computing techniques have been applied in the area of data mining either to optimize the parameters of data mining algorithms or to discover knowledge or patterns in the data, i.e., to directly solve the target data mining problem. This book proposes a different goal for evolutionary algorithms in data mining: to automate the design of a data mining algorithm, rather than just optimize its parameters.The authors first offer introductory overviews on data mining, focusing on rule induction methods, and on evolutionary algorithms, focusing on genetic programming. They then examine the conventional use of evolutionary algorithms to discover classification rules or related types of knowledge structures in the data, before moving to the more ambitious objective of their research, the design of a new genetic programming system for automating the design of full rule induction algorithms. They analyze computational results from their automatically designed algorithms, which show that the machine-designed rule induction algorithms are competitive when compared with state-of-the-art human-designed algorithms. Finally the authors examine future research directions.This book will be useful for researchers and practitioners in the areas of data mining and evolutionary computation.PPN: PPN: 1649968329Package identifier: Produktsigel: ZDB-2-SCS
Preface; Contents; Acronyms; Introduction; Data Mining; Evolutionary Algorithms; Genetic Programming for Classification and Algorithm Design; Automating the Design of Rule Induction Algorithms; Computational Results on the Automatic Design of Full Rule Induction Algorithms; Directions for Future Research on the Automatic Design of Data Mining Algorithms; Index
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