Abstract
We have been coping with issues connected with non-deterministic information in rough sets. Non-deterministic information is a kind of incomplete information, and it defines a set in which the actual value exists, but we do not know which is the actual value. If the defined set is equal to the domain of attribute values, we may see this is corresponding to a missing value. We need to pick up the merits in each information, and need to apply them to analyzing data sets. In this paper, we describe our opinion on non-deterministic information as well as incomplete information, some algorithms, software tools, and its perspective in rough sets. © 2013 Springer-Verlag.
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Sakai, H., Wu, M., Yamaguchi, N., & Nakata, M. (2013). Non-deterministic information in rough sets: A survey and perspective. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8171 LNAI, pp. 7–15). https://doi.org/10.1007/978-3-642-41299-8_2
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