شماره ركورد كنفرانس :
144
عنوان مقاله :
BeeMiner: A Novel Artificial Bee Colony Algorithmfor Classification Rule Discovery
پديدآورندگان :
Talebi Mahdi نويسنده Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, School of Medicine, Mashhad, Iran; , Abadi Mehdi نويسنده
كليدواژه :
Artificial Bee Colony , classification rule discovery , Data mining , Information theory
عنوان كنفرانس :
مجموعه مقالات دوازدهمين كنفرانس سيستم هاي هوشمند ايران
چكيده فارسي :
Artificial bee colony (ABC) is a new population-based
algorithm that has shown promising results in the field of optimization.
In this paper, we propose BeeMiner, a novel ABC algorithm
for discovering classification rules. BeeMiner differs from
the original ABC because it uses an information-theoretic heuristic
function (IHF) to guide the bees to search across the most
promising areas of the search space. We compare the performance
of BeeMiner with those of J48, JRip, and PART on nine
benchmark datasets from the UCI Machine Learning Repository.
The results show that BeeMiner is competitive with J48, JRip,
and PART in terms of the predictive accuracy
شماره مدرك كنفرانس :
3817034
