Jan. 2, 2024, 12:45 a.m. | matloff

R-bloggers www.r-bloggers.com

In my December 22 blog, I first introduced the classic parametric quantile regression (QR) concept. I then showed how one could use the qeML package to perform quantile regression nonparametrically, using the package’s qeKNN function for a k-Nearest Neighbors approach. A reader then asked if this could be applied to ...



Continue reading: Quantile Regression with Random Forests

blog concept forests function neighbors package parametric quantile random random forests r bloggers reading regression

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior Data Engineer

@ Quantexa | Sydney, New South Wales, Australia

Staff Analytics Engineer

@ Warner Bros. Discovery | NY New York 230 Park Avenue South