In view of the particularity of the value domains of mapping functions in soft sets, this paper presents data analysis approaches of soft sets under incomplete information. For standard soft sets, the decision value of an object with incomplete information is calculated by weighted-average of all possible choice values of the object, and the weight of each possible choice value is decided by the distribution of other objects. For fuzzy soft sets, incomplete data will be predicted based on the method of average-probability. Results of comparison show that comparing to other approaches for dealing with incomplete data, these approaches presented in this paper are preferable for reflecting actual states of incomplete data in soft sets. At last, an example is provided to illuminate the practicability and validity of the data analysis approach of soft sets under incomplete information.

Data analysis approaches of soft sets under incomplete information