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.
Editors: Komorowski, Jan and Zytkow, Jan.
| Title | Mining Time Series Using Rough Sets - A Case Study |
| Authors | Anders Torvill Bjorvand |
| Keywords | Rough sets, Time series |
| 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. |
| Category | Poster |
| Status | Accepted at PKDD'97 -- 1st European Symposium on Principles of Data Mining and Knowledge Discovery |
| Published | 1997, Springer Verlag, Lecture Notes in Artificial Intelligence 1263, pp. 351-358. Editors: Komorowski, Jan and Zytkow, Jan. |
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This document was last changed: 05/19/99 by Anders Torvill Bjorvand