A hybrid feature selection algorithm for the QSAR problem

Authors:
Marian Viorel Crăciun;Adina Cocu;Luminiţa Dumitriu;Cristina Segal
Affiliations:
Department of Computer Science and Engineering, University “Dunărea de Jos” of Galaţi, Romania;Department of Computer Science and Engineering, University “Dunărea de Jos” of Galaţi, Romania;Department of Computer Science and Engineering, University “Dunărea de Jos” of Galaţi, Romania;Department of Computer Science and Engineering, University “Dunărea de Jos” of Galaţi, Romania
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Year:
2006

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Abstract

In this paper we discuss a hybrid feature selection algorithm for the Quantitative Structure Activity Relationship (QSAR) modelling. This is one of the goals in Predictive Toxicology domain, aiming to describe the relations between the chemical structure of a molecule and its biological or toxicological effects, in order to predict the behaviour of new, unknown chemical compounds. We propose a hybridization of the ReliefF algorithm based on a simple fuzzy extension of the value difference metric. The experimental results both on benchmark and real world applications suggest more stability in dealing with noisy data and our preliminary tests give a promising starting point for future research.