2.5k citations · 2.9k across the 11 of their papers we have counts for
11 papers
Model-independent variable selection via the rule-based variable priority
Min Lu, Hemant Ishwaran
While achieving high prediction accuracy is a fundamental goal in machine learning, an equally important task is finding a small number of features with high explanatory power. One…
Dynamic Competing Risk Modeling COVID-19 in a Pandemic Scenario
Min Lu, Hemant Ishwaran
The emergence of coronavirus disease 2019 (COVID-19) in the United States has forced federal and local governments to implement containment measures. Moreover, the severity of the…
A Machine Learning Alternative to P-values
Min Lu, Hemant Ishwaran
This paper presents an alternative approach to p-values in regression settings. This approach, whose origins can be traced to machine learning, is based on the leave-one-out bootst…
Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods
Min Lu, Saad Sadiq, Daniel J. Feaster +1
Estimation of individual treatment effect in observational data is complicated due to the challenges of confounding and selection bias. A useful inferential framework to address th…
Random Forest Missing Data Algorithms
Fei Tang, Hemant Ishwaran
Random forest (RF) missing data algorithms are an attractive approach for dealing with missing data. They have the desirable properties of being able to handle mixed types of missi…
Boosted nonparametric hazards with time-dependent covariates
Donald K. K. Lee, Ningyuan Chen, Hemant Ishwaran
Given functional data from a survival process with time-dependent covariates, we derive a smooth convex representation for its nonparametric log-likelihood functional and obtain it…