DocumentCode
3216009
Title
Review on Ant Miners
Author
Panchal, V.K. ; Singh, Poonam ; Narula, Appoorv ; Mishra, Ashutosh
Author_Institution
DTRL Metcalfe House, Delhi, India
fYear
2009
fDate
9-11 Dec. 2009
Firstpage
1641
Lastpage
1644
Abstract
Extracting classification rules from data is an important task of data mining and is gaining considerable attention in recent years. This paper comprises classification of different types of rule extraction algorithm and their comparative study by considering their advantages separately. These Ant Colony based algorithms called as Ant_Miner have been successfully implemented in various fields such as remote sensing problems, combinatorial problems, scheduling problems and the quadratic assignment problem. No single algorithm is efficient enough to tackle related problems arising from different fields. Hence, in this paper we present several Ant_Miner algorithms which can be used according to one´s need.
Keywords
data mining; feature extraction; knowledge based systems; optimisation; pattern classification; Ant_Miner algorithm; ant colony optimization; classification rules extraction; data mining; rule extraction algorithm; Ant colony optimization; Artificial intelligence; Chemicals; Data mining; Image classification; Insects; Particle swarm optimization; Remote sensing; Satellites; Scheduling algorithm; Ant Colony Optimization (ACO); Ant_Miner; Classification of rules; Image Classification; data mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location
Coimbatore
Print_ISBN
978-1-4244-5053-4
Type
conf
DOI
10.1109/NABIC.2009.5393635
Filename
5393635
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