Abstract
Boosting is a bias reduction technique while bagging is a variance reduction method. These two methods aim at reducing the asymptotic mean integrated square error (AMISE). This study aims to show that bagging is a boosting algorithm in kernel density estimation since both techniques use large smoothing parameter(s). This relationship was verified by real and simulated data
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
