Abstract
We propose to use ILP techniques to learn sets of temporally constrained events called chronicles that a monitoring tool will use to detect pathological situations. ICL, a system providing a declarative bias language, was used for the experiments on learning cardiac arrhythmias. We show how to obtain properties, such as compactness, robustness or readability, by varying the learning bias.
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Quiniou, R., Cordier, MO., Carrault, G., Wang, F. (2001). Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition. In: Rouveirol, C., Sebag, M. (eds) Inductive Logic Programming. ILP 2001. Lecture Notes in Computer Science(), vol 2157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44797-0_18
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DOI: https://doi.org/10.1007/3-540-44797-0_18
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