23 citations · 23 across the 2 of their papers we have counts for
2 papers
cs.LG2018★ 23 cited
MEBoost: Mixing Estimators with Boosting for Imbalanced Data Classification
Farshid Rayhan, Sajid Ahmed, Asif Mahbub +4
Class imbalance problem has been a challenging research problem in the fields of machine learning and data mining as most real life datasets are imbalanced. Several existing machin…
cs.LG2017
LIUBoost : Locality Informed Underboosting for Imbalanced Data Classification
Sajid Ahmed, Farshid Rayhan, Asif Mahbub +4
The problem of class imbalance along with class-overlapping has become a major issue in the domain of supervised learning. Most supervised learning algorithms assume equal cardinal…