79 citations · 350 across the 23 of their papers we have counts for
Showing 2017 · cs.LGShow all
3 papers · 2 filters
cs.LG2017★ 4 cited
Proceedings of the IJCAI 2017 Workshop on Learning in the Presence of Class Imbalance and Concept Drift (LPCICD'17)
Shuo Wang, Leandro L. Minku, Nitesh Chawla +1
With the wide application of machine learning algorithms to the real world, class imbalance and concept drift have become crucial learning issues. Class imbalance happens when the…
cs.LG2017★ 4 cited
A Systematic Study of Online Class Imbalance Learning with Concept Drift
Shuo Wang, Leandro L. Minku, Xin Yao
As an emerging research topic, online class imbalance learning often combines the challenges of both class imbalance and concept drift. It deals with data streams having very skewe…
cs.LG2017★ 1 cited
Concept Drift Adaptation by Exploiting Historical Knowledge
Yu Sun, Ke Tang, Zexuan Zhu +1
Incremental learning with concept drift has often been tackled by ensemble methods, where models built in the past can be re-trained to attain new models for the current data. Two…