Release Time:2024-10-08  Hits:

Date of Publication: 2022-10-10

Journal: 微电子学与计算机

Institution: 软件学院

Issue: 7

Page Number: 167-172,176

ISSN: 1000-7180

Abstract: Existing incomplete data filling algorithm are all use the same method to fill all the missing values ,and did not consider the importance of each value , thus , makes all algorithms low efficiency and poor real - time . Therefore ,this paper proposes a new data filling algorithm based on distinguishing the importance of attributes ,it uses attribute reduction to distinguish important attributes and unimportant attributes ,then ,uses the improved mahalanobis - based algorithm to imputing the missing value that belong to the important attributes , and unimportant missing values according to the similarity -probabilistic method , thus ,ensure that the accuracy of data ,at the same time ,make sure the real -time and practicality .at last ,the experimental part using the Digital-home system and the UCI standard datasets to analysis the algorithm performance ,verifying the superiority of the algorithm .

Note: 新增回溯数据