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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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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
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365987163X
ISBN 13: 9783659871634
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar BhupendraDR 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 Ku. Bestandsnummer des Verkäufers 158430230
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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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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783659871634
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Attribute Selection with Genetic Algorithm
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ISBN 10: 365987163X
ISBN 13: 9783659871634
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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. Bestandsnummer des Verkäufers 9783659871634
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Attribute Selection with Genetic Algorithm
Verlag:
LAP Lambert Academic Publishing Mai 2016, 2016
ISBN 10: 365987163X
ISBN 13: 9783659871634
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 52 pp. Englisch. Bestandsnummer des Verkäufers 9783659871634
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Attribute Selection with Genetic Algorithm: Genetic Algorithm Based Attributes Subset Selection Using Naive Bays Classifier
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ISBN 10: 365987163X
ISBN 13: 9783659871634
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Attribute Selection with Genetic Algorithm: Genetic Algorithm Based Attributes Subset Selection Using Naive Bays Classifier
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365987163X
ISBN 13: 9783659871634
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