Data Analysis, Machine Learning and Knowledge Discovery

Häftad, Engelska, 2013

Del i serien Studies in Classification, Data Analysis, and Knowledge Organization

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2013-12-09
Mått:155 x 235 x 27 mm
Vikt:739 g
Format:Häftad
Språk:Engelska
Serie:Studies in Classification, Data Analysis, and Knowledge Organization
Antal sidor:470
Upplaga:2014
Förlag:Springer International Publishing AG
ISBN:9783319015941

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT
Försäljning och marknadsföring inom Ekonomi och Ledarskap

Recensioner i media

From the book reviews: "The book is organized in seven parts ... . The book is a very interesting collection of papers describing various approaches of data mining and machine learning on aspects from bioinformatics to music classification. It is an excellent addition to the field and it can be used as starting point for projects from undergraduate to post-graduate level." (Irina Ioana Mohorianu, zbMATH, Vol. 1301, 2015)

Innehållsförteckning

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.