2 citations · 3 across the 2 of their papers we have counts for
3 papers
stat.ME2020★ 2 cited
Multiple imputation using chained random forests: a preliminary study based on the empirical distribution of out-of-bag prediction errors
Shangzhi Hong, Yuqi Sun, Hanying Li +1
Missing data are common in data analyses in biomedical fields, and imputation methods based on random forests (RF) have become widely accepted, as the RF algorithm can achieve high…
stat.AP2020★ 1 cited
Influence of parallel computing strategies of iterative imputation of missing data: a case study on missForest
Shangzhi Hong, Yuqi Sun, Hanying Li +1
Machine learning iterative imputation methods have been well accepted by researchers for imputing missing data, but they can be time-consuming when handling large datasets. To over…
cs.LG2017
Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa
Michael T. Lash, Yuqi Sun, Xun Zhou +2
Neural networks are capable of learning rich, nonlinear feature representations shown to be beneficial in many predictive tasks. In this work, we use these models to explore the us…