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
Link To Document :
بازگشت