Data Analysis, Machine Learning and Knowledge Discovery

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing,...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Spiliopoulou, Myra (Editor ), Schmidt-Thieme, Lars (Editor ), Janning, Ruth (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Studies in Classification, Data Analysis, and Knowledge Organization,
Temas:
Mathematical statistics-Data processing.
Data mining.
Marketing.
Finance.
Biometry.
Psychology.
Statistics and Computing.
Data Mining and Knowledge Discovery.
Financial Economics.
Biostatistics.
Behavioral Sciences and Psychology.
Acceso en línea:Texto Completo
Descripción
Sumario:Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012.
Descripción Física:XXI, 470 p. 120 illus., 32 illus. in color. online resource.
ISBN:9783319015958
ISSN:2198-3321

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