A Novel Algorithm for Class Imbalance Learning on Big Data using Uniform Sampling Strategy (USS) Technique - Imran, Mohammad (International Journal of Computer Sciences and Engineering, 2025)
Big data consists of large volumes of data which are used to discover the hidden knowledge. Class imbalance nature is a conventional issue which is present in all real world datasets. The class imbalance nature in the big data reduces the performance of the existing classification algorithms. The data source of diverse nature available from varied sources also degrades the performance of the existing algorithms. To address these issues of class imbalance problem the present work proposed various novel and effective class imbalance learning (CIL) algorithms. In this work, we proposed Uniform Strategic Sampling (USS) Technique novel algorithms approaches for class imbalance data sources.