Computational Intelligence in Data Mining (Paperback, 2000 ed.)

The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline Discovering Structures in Large Databases the book starts with a unified view on Data Mining and Statistics - A System Point of View. Two special techniques follow: Subgroup Mining, and Data Mining with Possibilistic Graphical Models. Data Fusion and Possibilistic or Fuzzy Data Analysis is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on lernaing of fuzzy models is studied. In the domain of Classification and Decomposition adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section Learning and Data Fusion learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.

General

Imprint:	Springer-Verlag
Country of origin:	Austria
Series:	CISM International Centre for Mechanical Sciences, 408
Release date:	2001
First published:	2000
Editors:	Giacomo Della Riccia • Rudolf Kruse • Hans-J Lenz
Dimensions:	244 x 170 x 10mm (L x W x T)
Format:	Paperback
Pages:	166
Edition:	2000 ed.
ISBN-13:	978-3-211-83326-1
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-211-83326-9
Barcode:	9783211833261

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