12 citations · 14 across the 3 of their papers we have counts for
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stat.AP2019
Adjusting for Spatial Effects in Genomic Prediction
Xiaojun Mao, Somak Dutta, Raymond K. W. Wong +1
This paper investigates the problem of adjusting for spatial effects in genomic prediction. Despite being seldomly considered in genomic prediction, spatial effects often affect ph…
stat.ML2019★ 12 cited
Regression-Enhanced Random Forests
Haozhe Zhang, Dan Nettleton, Zhengyuan Zhu
Random forest (RF) methodology is one of the most popular machine learning techniques for prediction problems. In this article, we discuss some cases where random forests may suffe…