An incomplete data analysis approach using rough set theory
Weihua Zhu, Wei Zhang, Yunqing Fu · 2005
The “rough set” approach is an important tool to process uncertain or vague knowledge in AI applications. In this paper, the “rough set theory” is intensively researched and a concept of extended discemibility miitrix is introduced, which makes use of an algorithm “ROUSTIDA” to analyze incomplete data, which is based on “rough set theory”. The (advantage of this algorithm is that, it uses only the information given by the processed data and does not rely on other model assumptions. Experimental result shows this algorithm is efficient, comprehensible and adoptable for a pre-processing step before a data-mining method is emplqyed.