Publicado por LAP LAMBERT Academic Publishing Aug 2011, 2011
ISBN 10: 3845416203 ISBN 13: 9783845416205
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 49,00
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Knowledge discovery in data is called data mining. Many data mining techniques require classification and clustering. Large data sets are available nowadays in the world and fast approaches of classification or clustering becomes a tedious work with large data sets. For example, computer vision, text mining, semantic web mining, natural language processing etc., require non-parametric pattern recognition methods. This book describes fast approaches to discover knowledge from large data sets.This book deals with condensing of large data and also preserving essential information in the data. This book describes many efficient fast classifiers and clustering methods which are based on density information in the large data sets. It describes to resolve vagueness and uncertainty that is present in large data sets using combination principles of rough sets and fuzzy sets. Approaches in this book are adaptive and they can be applied in many machine learning methods in many domains.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch.
Publicado por Lap Lambert Academic Publishing, 2011
ISBN 10: 3845416203 ISBN 13: 9783845416205
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 97,82
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Añadir al carritoPaperback. Condición: Brand New. 116 pages. 8.66x5.91x0.27 inches. In Stock.
Publicado por Lap Lambert Academic Publishing, 2011
ISBN 10: 3845416203 ISBN 13: 9783845416205
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 104,90
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Añadir al carritoPaperback. Condición: Brand New. 116 pages. 8.66x5.91x0.27 inches. In Stock.
Publicado por LAP LAMBERT Academic Publishing Aug 2011, 2011
ISBN 10: 3845416203 ISBN 13: 9783845416205
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 49,00
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Knowledge discovery in data is called data mining. Many data mining techniques require classification and clustering. Large data sets are available nowadays in the world and fast approaches of classification or clustering becomes a tedious work with large data sets. For example, computer vision, text mining, semantic web mining, natural language processing etc., require non-parametric pattern recognition methods. This book describes fast approaches to discover knowledge from large data sets.This book deals with condensing of large data and also preserving essential information in the data. This book describes many efficient fast classifiers and clustering methods which are based on density information in the large data sets. It describes to resolve vagueness and uncertainty that is present in large data sets using combination principles of rough sets and fuzzy sets. Approaches in this book are adaptive and they can be applied in many machine learning methods in many domains. 116 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845416203 ISBN 13: 9783845416205
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 41,05
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Veluru SureshDr. Suresh Veluru is a postdoctoral fellow at University of New Brunswick,Canada.He received his PhD from Indian Institute of Technology Guwahati, India in 2009. Dr. P. Viswanath is a Professor and Dean R&D (El.
Publicado por LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845416203 ISBN 13: 9783845416205
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 49,00
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Knowledge discovery in data is called data mining. Many data mining techniques require classification and clustering. Large data sets are available nowadays in the world and fast approaches of classification or clustering becomes a tedious work with large data sets. For example, computer vision, text mining, semantic web mining, natural language processing etc., require non-parametric pattern recognition methods. This book describes fast approaches to discover knowledge from large data sets.This book deals with condensing of large data and also preserving essential information in the data. This book describes many efficient fast classifiers and clustering methods which are based on density information in the large data sets. It describes to resolve vagueness and uncertainty that is present in large data sets using combination principles of rough sets and fuzzy sets. Approaches in this book are adaptive and they can be applied in many machine learning methods in many domains.