Abstract
In this paper, the rule induction method STRIM, the classical Rough Sets (RS) theory and the notion of three-way decision rules are summarized and their performance is examined by applying them to a real-world dataset and a simulation dataset. From these experimental studies, the problems inherent in the rule induction method by the conventional RS theory based on the indiscernibility are pointed out and a comparison is made with STRIM. Specifically, the rule induction methods that are based on indiscernibility and do not consider the decision table which is only a sample of outcomes obtained by chance from a population of interest are highly dependent upon the samples in the decision table given. This paper states that such rule induction methods are thus problematic and need to be improved to create a more robust rule induction method.
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Saeki, T., Fei, J., Kato, Y. (2018). Considerations on Rule Induction Methods by the Conventional Rough Set Theory from a View of STRIM. In: Nguyen, H., Ha, QT., Li, T., Przybyła-Kasperek, M. (eds) Rough Sets. IJCRS 2018. Lecture Notes in Computer Science(), vol 11103. Springer, Cham. https://doi.org/10.1007/978-3-319-99368-3_16
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