International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 89 - Issue 5 |
Published: March 2014 |
Authors: Do Van Nguyen, Koichi Yamada, Muneyuki Unehara |
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Do Van Nguyen, Koichi Yamada, Muneyuki Unehara . Rough Sets and Rule Induction in Imperfect Information Systems. International Journal of Computer Applications. 89, 5 (March 2014), 1-8. DOI=10.5120/15495-4286
@article{ 10.5120/15495-4286, author = { Do Van Nguyen,Koichi Yamada,Muneyuki Unehara }, title = { Rough Sets and Rule Induction in Imperfect Information Systems }, journal = { International Journal of Computer Applications }, year = { 2014 }, volume = { 89 }, number = { 5 }, pages = { 1-8 }, doi = { 10.5120/15495-4286 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2014 %A Do Van Nguyen %A Koichi Yamada %A Muneyuki Unehara %T Rough Sets and Rule Induction in Imperfect Information Systems%T %J International Journal of Computer Applications %V 89 %N 5 %P 1-8 %R 10.5120/15495-4286 %I Foundation of Computer Science (FCS), NY, USA
The original rough set theory deals with precise and complete data, while real applications frequently contain imperfect information. A typical imperfect data studied in rough set research is the missing values. Though there are many ideas proposed to solve the issue in the literature, the paper adopts a probabilistic approach, because it can incorporate other types of imperfect data including imprecise and uncertain values in a single approach. The paper first discusses probabilities of attribute values assuming different type of attributes in real applications, and proposes a generalized method of probability of matching. This probability is then used to define valued tolerance/similarity relations and to develop new rough set models based on the valued tolerance/similarity relations. An algorithm for deriving decision rules based on the rough set models is also studied and proposed.