Scalable Non-Parametric Pattern Recognition Techniques for Data Mining : Fast Non-Parametric Classification and Clustering Methods for Large Data Sets
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Scalable Non-Parametric Pattern Recognition Techniques for Data Mining : Fast Non-Parametric Classification and Clustering Methods for Large Data Sets (2011)
~EN PB NWISBN: 9783845416205 bzw. 3845416203, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Druck auf Anfrage 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, Books.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Druck auf Anfrage 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, Books.
2
Scalable Non-Parametric Pattern Recognition Techniques for Data Mining (2011)
DE PB NWISBN: 9783845416205 bzw. 3845416203, in Deutsch, LAP LAMBERT Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Lieferbar in 2 - 3 Tage.
Fast Non-Parametric Classification and Clustering Methods for Large Data Sets 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. 02.08.2011, Taschenbuch.
Fast Non-Parametric Classification and Clustering Methods for Large Data Sets 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. 02.08.2011, Taschenbuch.
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Scalable Non-Parametric Pattern Recognition Techniques for Data Mining (2011)
DE PB NWISBN: 9783845416205 bzw. 3845416203, in Deutsch, LAP LAMBERT Academic Publishing, Taschenbuch, neu.
Lieferung aus: Schweiz, Versandfertig innert 3 - 5 Werktagen.
Fast Non-Parametric Classification and Clustering Methods for Large Data Sets, 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. Taschenbuch, 02.08.2011.
Fast Non-Parametric Classification and Clustering Methods for Large Data Sets, 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. Taschenbuch, 02.08.2011.
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Scalable Non-Parametric Pattern Recognition Techniques for Data Mining
DE NWISBN: 9783845416205 bzw. 3845416203, in Deutsch, neu.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, 11, zzgl. Versandkosten.
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.
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.
5
Scalable Non-Parametric Pattern Recognition Techniques for Data Mining - Fast Non-Parametric Classification and Clustering Methods for Large Data Sets
DE PB NWISBN: 9783845416205 bzw. 3845416203, in Deutsch, LAP Lambert Acad. Publ. Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Scalable Non-Parametric Pattern Recognition Techniques for Data Mining: 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. Englisch, Taschenbuch.
Scalable Non-Parametric Pattern Recognition Techniques for Data Mining: 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. Englisch, Taschenbuch.
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Scalable Non-Parametric Pattern Recognition Techniques for Data Mining: Fast Non-Parametric Classification and Clustering Methods for Large Data Sets (2011)
DE PB NW RPISBN: 9783845416205 bzw. 3845416203, in Deutsch, LAP LAMBERT Academic Publishing, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, English-Book-Service - A Fine Choice [1048135], Waldshut-Tiengen, Germany.
This item is printed on demand for shipment within 3 working days.
This item is printed on demand for shipment within 3 working days.
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Scalable Non-Parametric Pattern Recognition Techniques for Data Mining
DE NWISBN: 3845416203 bzw. 9783845416205, in Deutsch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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Scalable Non-Parametric Pattern (2011)
DE PB NWISBN: 9783845416205 bzw. 3845416203, in Deutsch, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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