Approach to Missing Data Recovery

Abstract

In order to recover the missing data in an information system, the paper proposed a new approach based on rough set to reduce the redundant attributes, discretize the continuous attributes and fill in the missing data. According to indiscernible relationship, discernible vector were defined and used the discernible vector addition rule to reduce attributes. And then, depending on the concept of super-club data and entropy of the information table, discretization of the continuous attributes was implemented. Finally, by use of the corresponding relationship of condition attributes and decision attributes, the definition of interval value and interval value addition rule were defined and filled up the incomplete data. The illustration and experimental results indicate that the approach is effective and efficient.