Myra Spiliopoulou & Lars Schmidt-Thieme 
Data Analysis, Machine Learning and Knowledge Discovery [PDF ebook] 

Soporte

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 (Gf Kl). The conference was held at the University of Hildesheim (Germany) in August 2012. ​

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Tabla de materias

AREA Statistics and Data Analysis: Classifcation, Cluster Analysis, Factor Analysis and Model Selection.- AREA Machine Learning and Knowledge Discovery: Clustering, Classifiers, Streams and Social Networks.- AREA Data Analysis and Classification in Marketing.- AREA Data Analysis in Finance.- AREA Data Analysis in Biostatistics and Bioinformatics.- AREA Interdisciplinary Domains: Data Analysis in Music, Education and Psychology.- LIS Workshop: Workshop on Classification and Subject Indexing in Library and Information Science.

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Idioma Inglés ● Formato PDF ● Páginas 470 ● ISBN 9783319015958 ● Tamaño de archivo 8.7 MB ● Editor Myra Spiliopoulou & Lars Schmidt-Thieme ● Editorial Springer International Publishing ● Ciudad Cham ● País CH ● Publicado 2013 ● Descargable 24 meses ● Divisa EUR ● ID 2854732 ● Protección de copia DRM social

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