Data Analysis of Clustering and Classification Schemes in Networking: Node stability analysis, NRGA and ELMKNN - Couverture souple

Sungheetha, Akey; Sharma, Rajesh

9786200467089: Data Analysis of Clustering and Classification Schemes in Networking: Node stability analysis, NRGA and ELMKNN

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ISBN 10 : 6200467080 ISBN 13 : 9786200467089

Editeur : LAP LAMBERT Academic Publishing, 2019

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2019
Langue: anglais
ISBN 10: 6200467080
ISBN 13: 9786200467089
Reliure: Broch�
Nombre de pages: 268
Coordonn�es du fabricant: non disponible
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Data Analysis of Clustering and Classification Schemes in Networking

Akey Sungheetha|Rajesh Sharma

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200467080 ISBN 13 : 9786200467089

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Etat : 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. N� de r�f. du vendeur 497402278

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Data Analysis of Clustering and Classification Schemes in Networking

Akey Sungheetha

Edit� par LAP LAMBERT Academic Publishing Nov 2019, 2019

ISBN 10 : 6200467080 ISBN 13 : 9786200467089

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Taschenbuch. Etat : 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. N� de r�f. du vendeur 9786200467089

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Data Analysis of Clustering and Classification Schemes in Networking : Node stability analysis, NRGA and ELMKNN

Akey Sungheetha

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200467080 ISBN 13 : 9786200467089

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Taschenbuch. Etat : 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. N� de r�f. du vendeur 9786200467089

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Data Analysis of Clustering and Classification Schemes in Networking

Akey Sungheetha

Edit� par LAP LAMBERT Academic Publishing Nov 2019, 2019

ISBN 10 : 6200467080 ISBN 13 : 9786200467089

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Taschenbuch. Etat : 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, �berseering 33, 22297 Hamburg 268 pp. Englisch. N� de r�f. du vendeur 9786200467089

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