Rough Sets in Knowledge Discovery 1: Methodology and Applications (Studies in Fuzziness and Soft Computing) (v. 1) - kelloggchurch.org

Oct 15, 1998 · Rough Sets in Knowledge Discovery 1: Methodology and Applications Studies in Fuzziness and Soft Computing v. 1 Hardcover – October 15, 1998 by Lech Polkowski Editor See all formats and editions Hide other formats and editions. The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles. Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies. Dec 01, 2010 · Rough set theory with applications to data mining. In Real World Applications of Computational Intelligence, Studies in Fuzziness and Soft Computing Series, Negoita, M. & Reusch, B. eds. Springer, Heidelberg, 223 – 244.

Bazan, J.G.: A comparison and non-dynamic rough set method for extracting laws decision tables. In: Polkowski, L., Skowron, A. eds. Rough Sets in Knowledge Discovery 1. Methodology and Applications, Studies in Fuzziness and Soft Computing, pp. 321–365. Physica-Verlag, Heidelberg 1998 Google Scholar. Rough set theory is a new mathematical approach to imperfect knowledge. The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. After probability theory, fuzzy set theory and evidence theory, rough set theory is a new mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge. In recent years, the research and applications on rough set theory have attracted more and more researchers' attention.

Rough set theory is a new mathematical approach to imperfect knowledge. The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. Recently it became also a crucial issue for computer scientists, particularly in the area of. May 19, 2009 · A. Øhrn, J. Komorowski 1997, ROSETTA: A Rough Set Toolkit for Analysis of Data, Proc. Third International Joint Conference on Information Sciences, Fifth International Workshop on Rough Sets and Soft Computing RSSC'97, Durham, NC, USA, March 1-5, Vol. 3, pp. 403-407. Jan 01, 2007 · L. Polkowski, A. Skowron Eds., Rough Sets in Knowledge Discovery 1: Methodology and Applications, Studies in Fuzziness and Soft Computing, vol. 18, Physica-Verlag, Heidelberg 1998 Google Scholar [59].

Rough set theory is a new mathematical approach to uncertain knowledge. The problem of imperfect or uncertain knowledge has been tackled by philosophers, mathematicians and logicians. Recently, in the area of artificial intelligence it too became a critical issue for computer scientists.

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