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Advanced Data Mining Techniques / by David L. Olson, Dursun Delen.

Por: Colaborador(es): Tipo de material: TextoTextoEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Descripción: recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783540769170
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • HF54.5-54.56
Recursos en línea:
Contenidos:
Data Mining Process -- Data Mining Methods As Tools -- Memory-Based Reasoning Methods -- Association Rules in Knowledge Discovery -- Fuzzy Sets in Data Mining -- Rough Sets -- Support Vector Machines -- Genetic Algorithm Support to Data Mining -- Performance Evaluation for Predictive Modeling -- Applications -- Applications of Methods.
Resumen: This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.
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Springer eBooks

Data Mining Process -- Data Mining Methods As Tools -- Memory-Based Reasoning Methods -- Association Rules in Knowledge Discovery -- Fuzzy Sets in Data Mining -- Rough Sets -- Support Vector Machines -- Genetic Algorithm Support to Data Mining -- Performance Evaluation for Predictive Modeling -- Applications -- Applications of Methods.

This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.

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