Automation of support ticket classification is crucial to improve customer support
performance and shortening resolution time for customer inquiries. This research aims to …

Imbalanced data poses a significant challenge in classification as model performance is af-
fected by insufficient learning from minority classes. Balancing methods are often used to …

Given a new class imbalanced dataset D and limited computational resources, the
challenge arises of selecting promising class imbalanced learning (CIL) pipelines that …

Abstract Existing Automated machine learning (AutoML) systems have achieved
considerable success in offline machine learning. Nonetheless, they are not applicable to …

Automated machine learning (AutoML) has achieved great success in offline class
imbalance learning where data are static. However, many real world applications data …

The intersection of predictive maintenance and Automated Machine Learning (AutoML)
ushers in a transformative era for industrial optimization, wherein the foresight of equipment …

In today's fast-paced corporate environment, efficient management of customer inquiries is
critical for maintaining high satisfaction and productivity levels. This study explores …

Both group bias and class imbalance occur when instances with certain characteristics are
under-represented in the data. Group bias causes estimators to be unfair and class …