A NEW HEURISTIC FUNCTION IN ANT-MINER APPROACH

Urszula Boryczka, Jan Kozak

2009

Abstract

In this paper, a novel rule discovery system that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants, where they search optimal solutions by considering both local heuristic and previous knowledge, observed by pheromone changes. In our approach we want to ensure the good performance of Ant-Miner by applying the new versions of heuristic functions in a main rule. We want to emphasize the role of the heuristic function by analyzing the influence of different propositions of these functions to the performance of Ant-Miner. The comparative study will be done using the 5 data sets from the UCI Machine Learning repository.

Paper Citation

in Harvard Style

Boryczka U. and Kozak J. (2009). A NEW HEURISTIC FUNCTION IN ANT-MINER APPROACH . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-85-2, pages 33-38. DOI: 10.5220/0001857700330038

in Bibtex Style

@conference{iceis09,
author={Urszula Boryczka and Jan Kozak},
title={A NEW HEURISTIC FUNCTION IN ANT-MINER APPROACH},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2009},
pages={33-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001857700330038},
isbn={978-989-8111-85-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A NEW HEURISTIC FUNCTION IN ANT-MINER APPROACH
SN - 978-989-8111-85-2
AU - Boryczka U.
AU - Kozak J.
PY - 2009
SP - 33
EP - 38
DO - 10.5220/0001857700330038