Self–Training With Quantile Errors for Multivariate Missing Data Imputation for Regression Problems in Electronic Medical Records: Algorithm Development Study

Self–Training With Quantile Errors for Multivariate Missing Data Imputation for Regression Problems in Electronic Medical Records: Algorithm Development Study

BackgroundWhen using machine learning in the real world, the missing value problem is the first problem encountered. Methods to impute this missing value include statistical methods such as mean, expectation-maximization, and multiple imputations by chained equations (MICE) a...

Full description

Bibliographic Details
Main Authors: Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Ha Na Cho, Heejung Choi, Tae Joon Jun, Young-Hak Kim
Format: Article
Language:English
Published: JMIR Publications 2021-10-01
Series:JMIR Public Health and Surveillance
Online Access:https://publichealth.jmir.org/2021/10/e30824

Internet

https://publichealth.jmir.org/2021/10/e30824

Similar Items