A conceptual model of enhanced undersampling technique
Maisarah Zorkeflee, Ku Ruhana Ku‐Mahamud, Aniza Mohamed Din · Universiti Utara Malaysia Institutional Repository (Universiti Utara Malaysia) · 2014
Imbalanced datasets often lead to decrement of classifiers’ performance.Undersampling technique is one of the approaches that is used when dealing with imbalanced datasets problem.This paper discusses on the advantages and disadvantages of several undersampling techniques.An enhanced Distancebased undersampling technique is proposed to balance the imbalanced data that will be used for classification. The fuzzy logic has been integrated in the distance-based undersampling technique to resolve the ambiguity and bias issues.