408 citations · 695 across the 22 of their papers we have counts for
5 papers · 1 filter
bartMachine: Machine Learning with Bayesian Additive Regression Trees
Adam Kapelner, Justin Bleich
We present a new package in R implementing Bayesian additive regression trees (BART). The package introduces many new features for data analysis using BART such as variable selecti…
Variable selection for BART: An application to gene regulation
Justin Bleich, Adam Kapelner, Edward I. George +1
We consider the task of discovering gene regulatory networks, which are defined as sets of genes and the corresponding transcription factors which regulate their expression levels.…
Peeking Inside the Black Box: Visualizing Statistical Learning with Plots of Individual Conditional Expectation
Alex Goldstein, Adam Kapelner, Justin Bleich +1
This article presents Individual Conditional Expectation (ICE) plots, a tool for visualizing the model estimated by any supervised learning algorithm. Classical partial dependence…
Prediction with Missing Data via Bayesian Additive Regression Trees
Adam Kapelner, Justin Bleich
We present a method for incorporating missing data in non-parametric statistical learning without the need for imputation. We focus on a tree-based method, Bayesian Additive Regres…
Matching on-the-fly in Sequential Experiments for Higher Power and Efficiency
Adam Kapelner, Abba Krieger
We propose a dynamic allocation procedure that increases power and efficiency when measuring an average treatment effect in sequential randomized trials. Subjects arrive iterativel…