Deep learning versus conventional methods for missing data imputation: A review and comparative study-Reference-Cited by-同舟云学术

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Deep learning versus conventional methods for missing data imputation: A review and comparative study

Published:2023-10 Issue: Volume:227 Page:120201
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Sun Yige,Li Jing^ORCID,Xu Yifan,Zhang Tingting^ORCID,Wang Xiaofeng^ORCID

Funder

National Science Foundation

National Institutes of Health

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference36 articles.

1. TensorFlow: Large-scale machine learning on heterogeneous systems;Abadi,2015

2. Categorical data analysis;Agresti,2003

3. A study of K-nearest neighbour as an imputation method;Batista;HIS - Frontiers in Artificial Intelligence and Applications,2002

4. Mice: Multivariate imputation by chained equations inR;Buuren;Journal of Statistical Software,2011

5. Microeconometrics: Methods and applications;Cameron,2005

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