The yearly increase in incidents of credit card fraud can be attributed to the rapid growth of e-
commerce. To address this issue, effective fraud detection methods are essential. Our …

Credit card fraud is a pervasive issue that causes significant financial loss, thus
underscoring the urgent need for effective detection techniques. In this book chapter on One …

Machine learning research on Medicare fraud detection is of national importance, primarily
due to the extensive financial losses caused by this deceptive practice. Our big data study …

Research into Medicare fraud detection that utilizes machine learning methodologies is of
great national interest due to the significant fiscal ramifications of this type of fraud. Our big …

Acquiring labeled datasets often incurs substantial costs primarily due to the requirement of
expert human intervention to produce accurate and reliable class labels. In the modern data …

Abstract According to the World Health Organization (WHO), there are around 7 million
breast cancer patients each year, with about 5 million of them dying. Based on Globocan …

Multi-view imbalanced learning is to handle the datasets with multi-view representations and
imbalanced classes. Existing multi-view imbalanced learning methods can be divided into …

Offline policy learning aims to discover decision-making policies from previously-collected
datasets without additional online interactions with the environment. As the training dataset …

This research classifies acoustic instruments using Convolutional Neural Network (CNN).
We utilize a dataset from Kaggle containing audio recordings of piano, violin, drums, and …

Average hold time is a concern for call centers because it affects customer satisfaction.
Contact centers should instruct their agents to use special on-hold scripts to maintain …