DC* (Double Clustering with A*) is an algorithm capable of generating highly interpretable fuzzy information granules from preclassified data. These information granules can be used as bulding-blocks for fuzzy rule-based classifiers that exhibit a good tradeoff between interpretability and accuracy. DC* relies on A* for the granulation process, whose efficiency is tightly related to the heuristic function used for estimating the costs of candidate solutions. In this paper we propose a new heuristic function that is capable of exploiting class information to overcome the heuristic function originally used in DC* in terms of efficiency. The experimental results show that the proposed heuristic function allows huge savings in terms of computational effort, thus making DC* a competitive choice for designing interpretable fuzzy rule-based classifiers.

A new heuristic function for DC*

MENCAR, CORRADO;CASTIELLO, CIRO;FANELLI, Anna Maria
2013-01-01

Abstract

DC* (Double Clustering with A*) is an algorithm capable of generating highly interpretable fuzzy information granules from preclassified data. These information granules can be used as bulding-blocks for fuzzy rule-based classifiers that exhibit a good tradeoff between interpretability and accuracy. DC* relies on A* for the granulation process, whose efficiency is tightly related to the heuristic function used for estimating the costs of candidate solutions. In this paper we propose a new heuristic function that is capable of exploiting class information to overcome the heuristic function originally used in DC* in terms of efficiency. The experimental results show that the proposed heuristic function allows huge savings in terms of computational effort, thus making DC* a competitive choice for designing interpretable fuzzy rule-based classifiers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/114043
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