Abstract
Toxicity characterization of chemicals’ emissions is a complex task which proceeds via multimedia fate and exposure models attached to models of dose–response relationships. Several different environmental multimedia models exist, but in any case a vast amount of data on the properties of the chemical compounds being assessed is required. This paper deals with the selection of informative variables in the problem of deriving characterization factors for eco-toxicology and human toxicology of chemical compounds starting from molecular-based properties. The Gamma Test algorithm has been applied to single out the most informative variables. The set of variables retained varies with the subset of the original dataset used to carry out the analysis. In particular, 16 different subsets have been used. They have been created selecting each time only those entries in the data set where one chosen input variable was available only from measurements/estimations, respectively.
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Marvuglia, A., Kanevski, M., Leuenberger, M., Benetto, E. (2014). Variables Selection for Ecotoxicity and Human Toxicity Characterization Using Gamma Test. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8581. Springer, Cham. https://doi.org/10.1007/978-3-319-09150-1_47
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DOI: https://doi.org/10.1007/978-3-319-09150-1_47
Publisher Name: Springer, Cham
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