Title: Experiments in predicting biodegradability
Authors: Blockeel, Hendrik ×
Dzeroski, Saso
Kompare, Boris
Kramer, Stefan
Pfahringer, Bernhard
Van Laer, Wim #
Issue Date: Feb-2004
Publisher: Taylor & francis inc
Series Title: Applied artificial intelligence vol:18 issue:2 pages:157-181
Abstract: This paper is concerned with the use of AI techniques in ecology. More specifically, we present a novel application of inductive logic programming (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 for aerobic aqueous biodegradation. Structural descriptions of chemicals in terms of atoms and bonds are derived from the chemicals' SMILES encodings. The definition of substructures is used as background knowledge. Predicting biodegradability is essentially a regression problem, but we also consider a discretized version of the target variable. We thus employ a number of relational classification and regression methods on the relational representation and compare these to propositional methods applied to different propositionalizations of the problem. We also experiment with a prediction technique that consists of merging upper and lower bound predictions into one prediction. Some conclusions are drawn concerning the applicability of machine learning systems and the merging technique in this domain and the evaluation of hypotheses.
ISSN: 0883-9514
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Informatics Section
× corresponding author
# (joint) last author

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