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Scalable Non-Parametric Pattern Recognition Techniques for Data Mining: Fast Non-Parametric Classification and Clustering Methods for Large Data Sets - Tapa blanda

 
9783845416205: Scalable Non-Parametric Pattern Recognition Techniques for Data Mining: Fast Non-Parametric Classification and Clustering Methods for Large Data Sets

Sinopsis

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.

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Reseña del editor

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.

Biografía del autor

Dr. 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 (Electrical Sciences) at Rajeev Gandhi Memorial College of Eng. & Tech., Nandyal. He received his PhD from IISc, Bangalore,India.

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Suresh Veluru
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Taschenbuch. 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. Nº de ref. del artículo: 9783845416205

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Condición: 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. Nº de ref. del artículo: 5481393

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Taschenbuch. 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. Nº de ref. del artículo: 9783845416205

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Taschenbuch. 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. Nº de ref. del artículo: 9783845416205

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Veluru, Suresh; Pulabaigari, Viswanath; Veluru, Suresh; Pulabaigari, Viswanath
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Veluru, Suresh; Pulabaigari, Viswanath; Veluru, Suresh; Pulabaigari, Viswanath
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ISBN 10: 3845416203 ISBN 13: 9783845416205
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