Applying rough sets to data tables containing imprecise information under probabilistic interpretation

  • Authors:
  • Michinori Nakata;Hiroshi Sakai

  • Affiliations:
  • Faculty of Management and Information Science, Josai International University, Togane, Chiba, Japan;Department of Mathematics and Computer Aided Sciences, Faculty of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, Japan

  • Venue:
  • RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Rough sets are applied to data tables containing imprecise information under probabilistic interpretation. A family of weighted equivalence classes is obtained, in which each equivalence class is accompanied by the probabilistic degree to which it is an actual one. By using the family of weighted equivalence classes we can derive a lower approximation and an upper approximation. The lower approximation and the upper approximation coincide with those obtained from methods of possible worlds.