Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
Da: Books Puddle, New York, NY, U.S.A.
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 620047544X ISBN 13: 9786200475442
Da: Books Puddle, New York, NY, U.S.A.
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 620047544X ISBN 13: 9786200475442
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Aggiungi al carrelloPaperback. Condizione: Brand New. 232 pages. 8.66x5.91x0.53 inches. In Stock.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Nov 2019, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -In MANET, EOPHMR approach has been used to conserve energy in the nodes. The energy reduction of the proposed EOPHMR approach is observed to be significant.A clustering algorithm that is a hybrid model of IG NRGA and KNN is presented for feature selection in microarray data sets. NRGA algorithm is used to do feature selection based on clustering technique. The approach uses ELM and FKNN as classifiers. The objective of the proposed systems is to get the highest accuracy when classifying the samples by the means a small subset of informative genes. A combination of two proposed gene selection techniques is used to solve the problem of the microarray high dimensionality. The combined technique gives high performance as it reduces the amount genes. It chooses gene for classification as each of them are much efficient binary classification techniques and typically give good results by attenuating their variety of attributes.Books on Demand GmbH, Überseering 33, 22297 Hamburg 268 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Nov 2019, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In MANET, EOPHMR approach has been used to conserve energy in the nodes. The energy reduction of the proposed EOPHMR approach is observed to be significant.A clustering algorithm that is a hybrid model of IG NRGA and KNN is presented for feature selection in microarray data sets. NRGA algorithm is used to do feature selection based on clustering technique. The approach uses ELM and FKNN as classifiers. The objective of the proposed systems is to get the highest accuracy when classifying the samples by the means a small subset of informative genes. A combination of two proposed gene selection techniques is used to solve the problem of the microarray high dimensionality. The combined technique gives high performance as it reduces the amount genes. It chooses gene for classification as each of them are much efficient binary classification techniques and typically give good results by attenuating their variety of attributes. 268 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 620047544X ISBN 13: 9786200475442
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharma RajeshI am Dr. Rajesh Sharma Rajendran, Working as assistant professor in school of Electrical Engineering and Computing, Adama Science and Technology University, Adama,Ethiopia.I have recieved my Ph.D from Anna University,Ind.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sungheetha AkeyThe academic work habits have evolved over the past eleven years on teaching and research. Significant contributions have been made based on the study that illustrates a unique pattern of data analysis. The study reave.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
Da: Majestic Books, Hounslow, Regno Unito
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Aggiungi al carrelloCondizione: New. Print on Demand.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 620047544X ISBN 13: 9786200475442
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Lingua: Inglese
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ISBN 10: 6200467080 ISBN 13: 9786200467089
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Data Analysis of Clustering and Classification Schemes in Networking | Node stability analysis, NRGA and ELMKNN | Akey Sungheetha (u. a.) | Taschenbuch | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200467089 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200467080 ISBN 13: 9786200467089
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 83,89
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In MANET, EOPHMR approach has been used to conserve energy in the nodes. The energy reduction of the proposed EOPHMR approach is observed to be significant.A clustering algorithm that is a hybrid model of IG NRGA and KNN is presented for feature selection in microarray data sets. NRGA algorithm is used to do feature selection based on clustering technique. The approach uses ELM and FKNN as classifiers. The objective of the proposed systems is to get the highest accuracy when classifying the samples by the means a small subset of informative genes. A combination of two proposed gene selection techniques is used to solve the problem of the microarray high dimensionality. The combined technique gives high performance as it reduces the amount genes. It chooses gene for classification as each of them are much efficient binary classification techniques and typically give good results by attenuating their variety of attributes.