Survey on Highly Imbalanced Multi-class Data

Machine learning technology has a massive impact on society because it offers solutions to solve many complicated problems like classification, clustering analysis, and predictions, especially during the COVID-19 pandemic. Data distribution in machine been an essential aspect providing unbiased solutions. From earliest literatures published highly imbalanced data until recently, research focused mostly binary classification problems. Research multi-class is still greatly unexplored when need for better analysis predictions handling Big required. This study focuses reviews related models or techniques data, along with their strengths weaknesses domains. Furthermore, paper uses statistical method explore case severely dataset. article aims (1) understand trend of through literatures; (2) analyze previous current methods data; (3) construct framework data. The chosen dataset will also be performed adapted learning, followed by discussions open challenges future direction Finally, this presents novel framework. We hope can provide insights potential development handle manipulate