A replica analysis of under-bagging

arXiv:2404.09779v1 Announce Type: cross
Abstract: A sharp asymptotics of the under-bagging (UB) method, which is a popular ensemble learning method for training classifiers from an imbalanced data, is derived and used to compare with several other standard methods for learning from imbalanced data, in the scenario where a linear classifier is trained from a binary mixture data. The methods compared include the under-sampling (US) method, which trains a model using a single realization of the subsampled dataset, and the simple …

abstract analysis arxiv binary classifier classifiers cond-mat.dis-nn cond-mat.stat-mech cs.lg data ensemble linear popular replica standard stat.ml training type