This paper presents a study of the user-defined parameters of the cAnt-Miner2 algorithm which extended the approach of coping with continuous attributes that was introduced by the cAnt-Miner algorithm. Experiments on two public medical data sets were carried out, in order to find appropriate parameter combinations for different classification problems. The experiments highlight the influence of each parameter and their combinations on the cAnt-Miner2 algorithm, in terms of accuracy, simplicity and computational cost.
['Ioannis Michelakos', 'Elpiniki I. Papageorgiou', 'Michael Vasilakopoulos']
A Study of cAnt-Miner2 Parameters Using Medical Data Sets