A Practical Guide to Data Mining for Business and Industry.

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Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is c...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ahlemeyer-Stubbe, Andrea
Otros Autores: Coleman, Shirley
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken : Wiley, 2014.
Temas:
Data mining.
Marketing > Data processing.
Management > Mathematical models.
Data Mining
Exploration de données (Informatique)
Marketing > Informatique.
Gestion > Modèles mathématiques.
Data mining
Management > Mathematical models
Marketing > Data processing
Acceso en línea:Texto completo
Descripción
Sumario:Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method.
Notas:5 Analytics.
Descripción Física:1 online resource (325 pages)
Bibliografía:Includes bibliographical references and index.
ISBN:9781118763728
1118763726

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