Missing value imputation using a novel grey based fuzzy c-means, mutual information based feature selection, and regression model
作者：
Highlights：
• A new hybrid method for the imputation of missing values is proposed.
• The method is based on a novel fuzzy c-means, mutual information, and regression.
• Performance of imputation increases by using Grey in the fuzzy c-means algorithm.
• The proposed method outperforms five existing imputation methods, in most cases.
• The proposed method can also provide high classification accuracies.
摘要
•A new hybrid method for the imputation of missing values is proposed.•The method is based on a novel fuzzy c-means, mutual information, and regression.•Performance of imputation increases by using Grey in the fuzzy c-means algorithm.•The proposed method outperforms five existing imputation methods, in most cases.•The proposed method can also provide high classification accuracies.
论文关键词：Missing data imputation,Grey relational analysis,Fuzzy c-means,Mutual information,Regression
论文评审过程：Received 6 January 2018, Revised 26 May 2018, Accepted 28 July 2018, Available online 30 July 2018, Version of Record 11 August 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.07.057
