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Date of Publication:2022-10-10

Journal:微电子学与计算机

Affiliation of Author(s):软件学院

Issue:7

Page Number:167-172,176

ISSN No.: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