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Abstract. We present a novel application of inductive logic program-ming (ILP) in the area of quantitative structure-activity relationships (QSARs). The activity we want to predict is the biodegradability of chemical compounds in water. In particular, the target variable is the half-life in water for aerobic aqueous biodegradation. Structural descrip-tions of chemicals in terms of atoms and bonds are derived from the chemicals ’ SMILES encodings. Denition of substructures are used as background knowledge. Predicting biodegradability is essentially a re-gression problem, but we also consider a discretized version of the target variable. We thus employ a number of relational classication and re-gression methods on the relational representation and compare these to propositional methods applied to dierent propositionalisations of the problem. Some expert comments on the induced theories are also given. 1
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Hendrik Blockeel
VIB-KU Leuven Center for Microbiology
Sašo Džeroski
Jožef Stefan Institute
Boris Kompare
University of Ljubljana
Applied Artificial Intelligence
KU Leuven
University of Ljubljana
Education New Zealand
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Blockeel et al. (Sun,) studied this question.
synapsesocial.com/papers/6a16d8437cba52b0f77ba705 — DOI: https://doi.org/10.1080/08839510490279131