ELMV: an Ensemble-Learning Approach for Analyzing Electrical Health Records with Significant Missing Values

no code implementations • 25 Jun 2020 • Lucas J. Liu, Hongwei Zhang, Jianzhong Di, Jin Chen

We propose a novel Ensemble-Learning for Missing Value (ELMV) framework, which introduces an effective approach to construct multiple subsets of the original EHR data with a much lower missing rate, as well as mobilizing a dedicated support set for the ensemble learning in the purpose of reducing the bias caused by substantial missing values.

Ensemble Learning Imputation