A Novel Data Filling Algorithm for Incomplete Information System Based on Valued Limited Tolerance Relation

Due to various reasons, there are generally missing data in datasets. Usually the missing data in these incomplete datasets need to be filled. In this paper, the drawbacks of some existing data filling approaches for incomplete information systems are analyzed based on Rough Set theory. Several similarity relation models are discussed and the Valued Limited Tolerance Relation model is proposed. A data filling algorithm based on the Valued Limited Tolerance Relation model is put forward. This approach makes full use of the similarity of objects and selects the object which is the most similar to the incomplete object. More missing data can be filled scientifically. The experimental results show that this approach is effective.