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Multi-objective evolutionary algorithms for knowledge discovery from databases

Author: Ashish Ghosh; Satchidananda Dehuri; Susmita Ghosh
Publisher: Berlin : Springer, ©2008.
Series: Studies in computational intelligence, v. 98.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the DM issues  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Multi-objective evolutionary algorithms for knowledge discovery from databases.
Berlin : Springer, ©2008
(OCoLC)209335645
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Ashish Ghosh; Satchidananda Dehuri; Susmita Ghosh
ISBN: 9783540774679 354077467X 9783540774662 3540774661
OCLC Number: 261324791
Description: 1 online resource (xiv, 159 pages) : illustrations.
Contents: Genetic algorithm for optimization of multiple objectives in knowledge discovery from large databases / Satchidananda Dehuri, Susmita Ghosh, Ashish Ghosh --
Knowledge incorporation in multi-objective evolutionary algorithms / Ricardo Landa-Becerra [and others] --
Evolutionary multi-objective rule selection for classification rule mining / Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima --
Rule extraction from compact pareto-optimal neural networks / Yaochu Jin, Bernhard Sendhoff, Edgar Körner --
On the usefulness of MOEAs for getting compact FRBSs under parameter tuning and rule selection / R. Alcalá [and others] --
Classification and survival analysis using multi-objective evolutionary algorithms / Christian Setzhorn --
Clustering based on genetic algorithms / M.N. Murty, Babaria Rashmin, Chiranjib Bhattacharyya.
Series Title: Studies in computational intelligence, v. 98.
Responsibility: Ashish Ghosh, Satchidananda Dehuri, Susmita Ghosh (eds.).
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Abstract:

A collection of seven articles containing research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases  Read more...

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