Edité par Bentham Science Publishers, 2024
ISBN 10 : 9815313045 ISBN 13 : 9789815313048
Langue: anglais
Vendeur : California Books, Miami, FL, Etats-Unis
EUR 55,45
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Edité par Bentham Science Publishers, 2024
ISBN 10 : 9815313045 ISBN 13 : 9789815313048
Langue: anglais
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 54,93
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Edité par LAP LAMBERT Academic Publishing Mär 2012, 2012
ISBN 10 : 3848438755 ISBN 13 : 9783848438754
Langue: anglais
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
EUR 49
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -The present study aimed to do the performance analysis of several data mining classification techniques using three different machine learning tools over the healthcare datasets. In this study, different data mining classification techniques have been tested on four different healthcare datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The experiments are done using the 10 fold cross validation method. A suitable technique for a particular dataset is chosen based on highest classification accuracy and least error rate.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch.
Edité par Amazon Digital Services LLC - Kdp, 2024
ISBN 10 : 9815313045 ISBN 13 : 9789815313048
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware - Federated Learning Based Intelligent Systems to Handle Issues and Challenges in IoVs (Part 1) examines how federated learning can address key challenges within the Internet of Vehicles, from data security to routing efficiency. This volume explores how federated learning, a decentralized approach to machine learning, enables secure and adaptive IoV systems that enhance road safety, optimize traffic flow, and support reliable data sharing.
Edité par LAP LAMBERT Academic Publishing Mrz 2012, 2012
ISBN 10 : 3848438755 ISBN 13 : 9783848438754
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
EUR 49
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present study aimed to do the performance analysis of several data mining classification techniques using three different machine learning tools over the healthcare datasets. In this study, different data mining classification techniques have been tested on four different healthcare datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The experiments are done using the 10 fold cross validation method. A suitable technique for a particular dataset is chosen based on highest classification accuracy and least error rate. 76 pp. Englisch.
Edité par LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3848438755 ISBN 13 : 9783848438754
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 41,05
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gupta ShellyShelly Gupta has done B.Tech. in IT from GJUS&T, India in 2009 & M.Tech. in CSE from Banasthali University, India in 2011. She has published 3 research papers at National /Intl level with 1 yr exp. in research. Her intere.
Edité par LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3848438755 ISBN 13 : 9783848438754
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 49
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The present study aimed to do the performance analysis of several data mining classification techniques using three different machine learning tools over the healthcare datasets. In this study, different data mining classification techniques have been tested on four different healthcare datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The experiments are done using the 10 fold cross validation method. A suitable technique for a particular dataset is chosen based on highest classification accuracy and least error rate.