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
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;
Conference_Titel :
Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4673-5164-5
DOI :
10.1109/ICDMW.2012.44
