Relational data mining applications: an overview
Relational Data Mining
Guest Editorial: Artificial Intelligence and Environmental Applications
Applied Intelligence
Artificial Intelligence and Environmental Decision Support Systems
Applied Intelligence
Sciences: environmental sciences
Handbook of data mining and knowledge discovery
An empirical study on sea water quality prediction
Knowledge-Based Systems
Greedy regression ensemble selection: Theory and an application to water quality prediction
Information Sciences: an International Journal
Ensembles of Multi-Objective Decision Trees
ECML '07 Proceedings of the 18th European conference on Machine Learning
Applying adaptive prediction to sea-water quality measurements
Expert Systems with Applications: An International Journal
Parallel ILP for distributed-memory architectures
Machine Learning
Constraint based induction of multi-objective regression trees
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Learning predictive clustering rules
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Tree ensembles for predicting structured outputs
Pattern Recognition
Multi-target regression with rule ensembles
The Journal of Machine Learning Research
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We address the problem of inferring chemical parameters of river water quality from biological ones. This task is important for enabling selective chemical monitoring of river water quality. We apply machine learning, in particular regression tree induction, to biological and chemical data on the water quality of Slovenian rivers. Regression trees are constructed that predict values of chemical parameters from data on the presence of bioindicator taxa at the species and family levels.