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Online tree-based ensembles and option trees for regression on evolving data streams.

, , and . Neurocomputing, (2015)

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Dynamical System Identification with Machine Learning, , and . Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications, page 50--63. Tahoe City, California, USA, (9 July 1995)Discovering Dynamics., and . ICML, page 97-103. Morgan Kaufmann, (1993)Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL., and . ML, page 399-402. Morgan Kaufmann, (1991)Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery., , and . MLSB, volume 8 of JMLR Proceedings, page 122-135. JMLR.org, (2010)Learning Rules for Early Diagnosis of Rheumatic Diseases., , , and . SCAI, volume 12 of Frontiers in Artificial Intelligence and Applications, page 138-149. IOS Press, (1991)Integrating Explanatory and Descriptive Learning in ILP., , and . IJCAI (2), page 900-907. Morgan Kaufmann, (1997)Discovering the Structure of Partial Differential Equations from Example Behaviour., , , , and . ICML, page 991-998. Morgan Kaufmann, (2000)Equation Discovery for Nonlinear System Identification., , , and . IEEE Access, (2020)Experiments In Predicting Biodegradability., , , , , and . Appl. Artif. Intell., 18 (2): 157-181 (2004)Discovering Dynamics: From Inductive Logic Programming to Machine Discovery., and . J. Intell. Inf. Syst., 4 (1): 89-108 (1995)