Computational Intelligence in Data Mining - CISM International Centre for Mechanical Sciences - G Della Riccia - Knjige - Springer Verlag GmbH - 9783211833261 - 31. maja 2000
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Computational Intelligence in Data Mining - CISM International Centre for Mechanical Sciences 2000 edition

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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.


Marc Notes: Includes bibliographical references; Contains papers accepted for final publication and read at the 3rd workshop on 'computational intelligence in data mining', Udine (Italy), Oct 8-10, 1998. Table of Contents: Data Mining and Statistics: a Systems Point of View (A. Siebes).- Subgroup Mining (W. Klosgen).- Possibilistic Graphical Models (C. Borgelt, J. Gebhardt, R. Kruse).- An Overview of Possibilistic Logic and its Application to Nonmonotonic Reasoning and Data Fusion (S. Benferhat, D. Dubois, H. Prade).- On the Solution of Fuzzy Equation Systems (H.-J. Lenz, R. Muller).- Learning Fuzzy Models and Potential Outliers (M. R. Berthold).- An Algorithm for Adaptive Clustering and Visualisation of Highdimensional Data Sets (F. Schwenker, H. A. Kestler, G. Palm).- Learning in Computer Soccer (H.-D. Burkhard).- Controlling Based on Stochastic Models (H.-J. Lenz, E. Rodel)."Publisher Marketing: 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 learning 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.

Contributor Bio:  Kruse, Rudolf Kruse-Univ. of Magdeburg, Germany

Medij Knjige     Paperback Book   (Knjiga z mehkimi platnicami in lepljenim hrbtom)
Izdano 31. maja 2000
ISBN13 9783211833261
Založniki Springer Verlag GmbH
Strani 166
Dimenzije 170 × 244 × 10 mm   ·   290 g
Jezik Francoščina  
Urednik Della Riccia, Giacomo
Urednik Kruse, Rudolf
Urednik Lenz, Hans-J.

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