Anzeige
Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Hybrid Feature Selection Algorithm for the QSAR Problem
verfasst von : Marian Viorel Crăciun, Adina Cocu, Luminiţa Dumitriu, Cristina Segal
Erschienen in: Computational Science – ICCS 2006
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.