DocumentCode
589190
Title
Towards a Particle Swarm Optimization-Based Regression Rule Miner
Author
Minnaert, Bart ; Martens, David
Author_Institution
Fac. of Econ. & Bus. Adm., Ghent Univ., Ghent, Belgium
fYear
2012
fDate
10-10 Dec. 2012
Firstpage
961
Lastpage
963
Abstract
We present the work in progress on a rule mining algorithm for regression using particle swarm optimization (PSO). Sub problems occuring during development involve the encoding of rules as particles and suitable PSO parameter tuning. A key subtask is the selection of a good rule learning heuristic. We introduce a novel heuristic for which preliminary results show promise.
Keywords
data mining; learning (artificial intelligence); particle swarm optimisation; regression analysis; PSO parameter tuning; key subtask; particle swarm optimization; regression algorithm; rule learning heuristic; rule mining algorithm; Data mining; Educational institutions; Linear programming; Measurement; Particle swarm optimization; Regression tree analysis; Training; heuristic; particle swarm optimization; regression; rule mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on
Conference_Location
Brussels
Print_ISBN
978-1-4673-5164-5
Type
conf
DOI
10.1109/ICDMW.2012.44
Filename
6406553
Link To Document