Abstract
The EC-Star rule-set representation is extended to allow probabilistic classifiers. This allows the distributed age-layered evolution of probabilistic rule sets. The method is tested on 20 UCI data problems, as well as a larger dataset of arterial blood pressure waveforms. Results show consistent improvement in all cases compared to binary classification rule-sets.
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Hodjat, B., Shahrzad, H., Miikkulainen, R., Murray, L., Holmes, C. (2018). PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification. In: Riolo, R., Worzel, B., Goldman, B., Tozier, B. (eds) Genetic Programming Theory and Practice XIV. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-319-97088-2_9
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DOI: https://doi.org/10.1007/978-3-319-97088-2_9
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