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Attribute Selection with Genetic Algorithm: Genetic Algorithm Based Attributes Subset Selection Using Naive Bays Classifier - Softcover
Inhaltsangabe
Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments.
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Reseña del editor
Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments.
Biografía del autor
DR Somesh Kumar presently spearheads the IT department in NIET, Gr. Noida, India. He has completed his MCA in 2000, ME (CS&E) in 2006, PhD (CS) in 2011. Since 2000, he has been in teaching profession. Prof Bhupendra Kumar currently workimg in IT department in NIET,Gr. Noida,INDIA. He has been in teaching profession from 2010.
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Attribute Selection with Genetic Algorithm: Genetic Algorithm Based Attributes Subset Selection Using Naive Bays Classifier
Verlag:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365987163X
ISBN 13: 9783659871634
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Paperback. Zustand: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock. Artikel-Nr. 365987163X
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Attribute Selection with Genetic Algorithm
Verlag:
LAP Lambert Academic Publishing Mai 2016, 2016
ISBN 10: 365987163X
ISBN 13: 9783659871634
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch. Artikel-Nr. 9783659871634
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