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Taschenbuch. Condition: Neu. Feature Selection in High Dimensional Data Using Metaheuristic | Haider Banka (u. a.) | Taschenbuch | 124 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330030633 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Published by LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330030631 ISBN 13: 9783330030633
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This books covers a state of the art literature on classical feature selection problem using some of the most recently developed methods. The feature selection problem has been investigated with great detail particularly in high dimensional space. The whole book consists of 7seven chapters covering many soft computing techniques such as PSO, GA, NSGA-II, ACO and others to deal with the feature selection problem. We hope that this edition will be more beneficial to all beginners, researchers and experts as well. 124 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330030631 ISBN 13: 9783330030633
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Published by LAP LAMBERT Academic Publishing, 2017
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Banka HaiderDr. Haider Banka received his Ph.D. in 2008 and joined in the Department of Computer Science and Engineering, Indian School of Mines, Dhanbad in the year 2007 and currently working as an Associate Professor. Dr. Banka has.
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Published by VDM Verlag Dr. Müller, 2010
ISBN 10: 3639264843 ISBN 13: 9783639264845
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Banka HaiderDr. Haider Banka is an Assistant Professor in the Department of Computer Science and Engineering, Indian School of Mines, Dhan- bad, India. He has more than 7 years of teaching and Research Experience and published mor.
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Published by LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330030631 ISBN 13: 9783330030633
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This books covers a state of the art literature on classical feature selection problem using some of the most recently developed methods. The feature selection problem has been investigated with great detail particularly in high dimensional space. The whole book consists of 7seven chapters covering many soft computing techniques such as PSO, GA, NSGA-II, ACO and others to deal with the feature selection problem. We hope that this edition will be more beneficial to all beginners, researchers and experts as well.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330030631 ISBN 13: 9783330030633
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This books covers a state of the art literature on classical feature selection problem using some of the most recently developed methods. The feature selection problem has been investigated with great detail particularly in high dimensional space. The whole book consists of 7seven chapters covering many soft computing techniques such as PSO, GA, NSGA-II, ACO and others to deal with the feature selection problem. We hope that this edition will be more beneficial to all beginners, researchers and experts as well.
Language: English
Published by VDM Verlag Dr. Müller, 2010
ISBN 10: 3639264843 ISBN 13: 9783639264845
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Hybridization using different soft computing tools has been explored for efficient data mining, clust- ering, and classification. An evolutionary-rough feature selection algorithm has been developed for feature selection and classi- fication of gene expre- ssion patterns. Next A detailed clustering algorithm is developed by integrating the advantage of both rough and fuzzy set theories. The remaining three chapters are devoted for biclustering problem. The whole work of this book is divided into the follow- ing: i) Mining important features from high dimen- sional gene datasets; ii) Biclustering or local stru- cture determination in gene expression data using soft tools; iii) Collaborative clustering for global structure determination in large data; iv) Covering various machine learning and bioinformatics applica- tions using soft computing; and v) A special chapter is written for designing a new paradigm for optimi- zation. The book focuses on some applications of the newly developed soft computing based methodologies for machine learning, optimization,and bioinformatic Problems. The book covers how to design a hybrid system for real life problem solving.