63 citations · 144 across the 6 of their papers we have counts for
3 papers · 1 filter
CUSBoost: Cluster-based Under-sampling with Boosting for Imbalanced Classification
Farshid Rayhan, Sajid Ahmed, Asif Mahbub +3
Class imbalance classification is a challenging research problem in data mining and machine learning, as most of the real-life datasets are often imbalanced in nature. Existing lea…
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…
iDTI-ESBoost: Identification of Drug Target Interaction Using Evolutionary and Structural Features with Boosting
Farshid Rayhan, Sajid Ahmed, Swakkhar Shatabda +4
Prediction of new drug-target interactions is extremely important as it can lead the researchers to find new uses for old drugs and to realize the therapeutic profiles or side effe…