Abstract
This article attempts to deal with the problem of time within the framework of rough sets. The rough set theory has emphasized the reduction of information necessary to acquire desired knowledge. This is particularly important when we are dealing with time. The farther back we are tracing our dependencies, the more attributes will become independent of our current decisions.
We formalize approaches to reasoning with time series where the sequence of events is important, and introduce formalisms to deduce decision rules with real-time constraints.
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© 1997 Springer-Verlag Berlin Heidelberg
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Bjorvand, A.T. (1997). Mining time series using rough sets — A case study. In: Komorowski, J., Zytkow, J. (eds) Principles of Data Mining and Knowledge Discovery. PKDD 1997. Lecture Notes in Computer Science, vol 1263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63223-9_134
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DOI: https://doi.org/10.1007/3-540-63223-9_134
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