KNN data filling method under incomplete fuzzy soft environments

Fuzzy soft set is a mathematical tool for dealing with uncertain information. Data omission can occur during data collection and transmission, leading to uncertainty and inaccuracy in information representation and processing. In this paper, a new KNN data filling method under incomplete fuzzy soft environments is proposed. The scheme calculates the distance between incomplete data rows and complete rows using complete data and sorts the distances. The K nearest neighbors are obtained, and the missing data are filled by the average of the K nearest neighbors. Finally the complete fuzzy soft set is obtained. And the feasibility of the method is verified by an example.