Journal of Chemical Information & Computer Sciences
Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Top-down induction of first-order logical decision trees
Artificial Intelligence
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
The predictive toxicology evaluation challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Demand-Driven Construction of Structural Features in ILP
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics
Computational Discovery of Scientific Knowledge
Top-Down Induction of Relational Model Trees in Multi-instance Learning
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Good and bad practices in propositionalisation
AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
From inductive logic programming to relational data mining
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Inductive queries on polynomial equations
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
InfraWatch: data management of large systems for monitoring infrastructural performance
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
A structural cluster kernel for learning on graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Relational Feature Mining with Hierarchical Multitask kFOIL
Fundamenta Informaticae - Machine Learning in Bioinformatics
Prediction of Ordinal Classes Using Regression Trees
Fundamenta Informaticae - Intelligent Systems
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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 in water for aerobic aqueous biodegradation. Structural descriptions of chemicals in terms of atoms and bonds are derived from the chemicals' SMILES encodings. Definition of substructures are 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 propositionalisations of the problem. Some expert comments on the induced theories are also given.