Evolutionary Machine Learning in Linguistic Knowledge Extraction
Lamiaa Ahmed
ISBN 10: 3659891037 ISBN 13: 9783659891038
Published by LAP LAMBERT Academic Publishing, 2016
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140 pages. 8.66x5.91x0.32 inches. In Stock. Seller Inventory # 3659891037
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This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets.
About the Author: Dr. Lamiaa H. Ahmed is a Lecturer of Computer Science at Modern Academy in Maadi, Cairo, Egypt. Computational Intelligence, Evolutionary Programming, Membrane Computing, Fuzzy Logic, Organic Computing and Java programming language are areas of interest.
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Bibliographic Details
Title: Evolutionary Machine Learning in Linguistic ...
Publisher: LAP LAMBERT Academic Publishing
Publication Date: 2016
Binding: Paperback
Condition: Brand New
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Evolutionary Machine Learning in Linguistic Knowledge Extraction
Published by
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ahmed LamiaaDr. Lamiaa H. Ahmed is a Lecturer of Computer Science at Modern Academy in Maadi, Cairo, Egypt. Computational Intelligence, Evolutionary Programming, Membrane Computing, Fuzzy Logic, Organic Computing and Java programming. Seller Inventory # 158248679
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Evolutionary Machine Learning in Linguistic Knowledge Extraction
Published by
LAP LAMBERT Academic Publishing Mai 2016, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
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Taschenbuch. Condition: Neu. Neuware -This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch. Seller Inventory # 9783659891038
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Evolutionary Machine Learning in Linguistic Knowledge Extraction
Published by
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets. Seller Inventory # 9783659891038
Quantity: 1 available
Seller Image
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Published by
LAP LAMBERT Academic Publishing Mai 2016, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets. 140 pp. Englisch. Seller Inventory # 9783659891038
Quantity: 2 available