A fundamental concern in the Quantitative Structure-Activity Relationship approach to toxicity evaluation is the generalization of the model over a wide range of compounds. The data driven modelling of toxicity, due to the complex and ill-defined nature of eco-toxicological systems,
is an uncertain process. The development of a toxicity predicting model without considering uncertainties may produce a model with a low generalization performance. This study presents a novel approach to toxicity modelling that handles the involved uncertainties using a fuzzy filter, and
thus improves the generalization capability of the model. The method is illustrated by considering a data set dealing with the fathead minnow (Pimephales promelas) toxicity of 568 organic compounds.
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Document Type: Research Article
Institute of Chemistry, University of Rostock, Rostock, Germany
Centre for Life Science Automation, Rostock, Germany
Institute of Preventive Medicine, University of Rostock, Rostock, Germany
Publication date: December 1, 2007