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.

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Product Description

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.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Austria

Series

CISM International Centre for Mechanical Sciences, 408

Release date

2001

Availability

Expected to ship within 10 - 15 working days

First published

2000

Editors

, ,

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

Barcode

9783211833261

Categories

LSN

3-211-83326-9



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