Rough classification in incomplete information systems

This paper investigates the case of incomplete information systems, and presents a generalization of the rough sets approach which deals with missing and imprecise descriptors.

Abstract

The paper is concerned with the problems of rough sets theory and rough classification of objects. It is a new approach to problems from the field of decision-making, data analysis, knowledge representation, expert systems etc. Several applications (particularly in medical diagnosis and engineering control) confirm the usefulness of the rough sets idea. Rough classification concerns objects described by multiple attributes in a so-called information system. Traditionally, the information system is assumed to be complete, i.e. the descriptors are not missing and are supposed to be precise. In this paper we investigate the case of incomplete information systems, and present a generalization of the rough sets approach which deals with missing and imprecise descriptors.