Artículos relacionados a Advances in K-means Clustering: A Data Mining Thinking...
Sinopsis
Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.
"Sinopsis" puede pertenecer a otra edición de este libro.
De la contraportada
Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer
- Año de publicación2012
- ISBN 10 3642298060
- ISBN 13 9783642298066
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de páginas196
- Contacto del fabricanteno disponible
Comprar nuevo
Ver este artículo
EUR 92,27
EUR 19,49 gastos de envío desde Alemania a España
Destinos, gastos y plazos de envíoOtras ediciones populares con el mismo título
Resultados de la búsqueda para Advances in K-means Clustering: A Data Mining Thinking...
Imagen de archivo
Advances in K-means Clustering : A Data Mining Thinking
Publicado por
Springer Berlin Heidelberg, 2012
ISBN 10: 3642298060
ISBN 13: 9783642298066
Antiguo o usado
Tapa dura
Librería: Buchpark, Trebbin, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: Sehr gut. Zustand: Sehr gut | Seiten: 196 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 12301636/12
Cantidad disponible: 1 disponibles
Imagen del vendedor
Advances in K-means Clustering
Publicado por
Springer Berlin Heidelberg, 2012
ISBN 10: 3642298060
ISBN 13: 9783642298066
Nuevo
Tapa dura
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gives an overall picture on how to adapt K-means to the clustering of newly emerging big dataEstablishes a theoretical framework for K-means clustering and cluster validityStudies the dangerous uniform effect and zero-value dilemma of K-mea. Nº de ref. del artículo: 5056029
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Advances in K-means Clustering
Publicado por
Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2012, 2012
ISBN 10: 3642298060
ISBN 13: 9783642298066
Nuevo
Tapa dura
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this 'old' algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the 'dangerous' uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the '2010 National Excellent Doctoral Dissertation Award', the highest honor for not more than 100 PhD theses per year in China. 196 pp. Englisch. Nº de ref. del artículo: 9783642298066
Cantidad disponible: 2 disponibles
Imagen del vendedor
Advances in K-means Clustering : A Data Mining Thinking
Publicado por
Springer Berlin Heidelberg, 2012
ISBN 10: 3642298060
ISBN 13: 9783642298066
Nuevo
Tapa dura
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this 'old' algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the 'dangerous' uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the '2010 National Excellent Doctoral Dissertation Award', the highest honor for not more than 100 PhD theses per year in China. Nº de ref. del artículo: 9783642298066
Cantidad disponible: 1 disponibles
Imagen de archivo
Advances in K-means Clustering: A Data Mining Thinking (Springer Theses: Recognizing Outstanding Ph.D. Research)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. In. Nº de ref. del artículo: ria9783642298066_new
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Advances in K-Means Clustering : A Data Mining Thinking
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 17845286-n
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Advances in K-means Clustering
Publicado por
Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2012, 2012
ISBN 10: 3642298060
ISBN 13: 9783642298066
Nuevo
Tapa dura
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this 'old' algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the 'dangerous' uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the '2010 National Excellent Doctoral Dissertation Award', the highest honor for not more than 100 PhD theses per year in China.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch. Nº de ref. del artículo: 9783642298066
Cantidad disponible: 2 disponibles
Imagen del vendedor
Advances in K-Means Clustering : A Data Mining Thinking
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 17845286
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Advances in K-Means Clustering : A Data Mining Thinking
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 17845286
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Advances in K-Means Clustering : A Data Mining Thinking
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 17845286-n
Cantidad disponible: Más de 20 disponibles