The classification of imbalanced datasets is a prominent task in text mining and machine
learning. The number of samples in each class is not uniformly distributed; one class …

Class imbalance is a common issue while develo** classification models. In order to
tackle this problem, synthetic data have recently been developed to enhance the minority …

To understand the mechanism of biological processes inside a human, it is necessary to
look at its various regulatory aspects, such as DNA methylation and post-translational …

Software failures inform engineering work, standards, regulations. For example, the Log4J
vulnerability brought government and industry attention to evaluating and securing software …

Palmprint recognition has emerged as a prominent biometric technology, widely applied in
diverse scenarios. Traditional handcrafted methods for palmprint recognition often fall short …

The rapid evolution of cyber threats requires proactive and automated detection
mechanisms. Although machine learning shows potential in this area, current models …

Large-truck crashes often result in substantial economic and social costs. Accurate
prediction of the severity level of a reported truck crash can help rescue teams and …

With the expansion of data availability, machine learning (ML) has achieved remarkable
breakthroughs in both academia and industry. However, imbalanced data distributions are …

This study explores a machine learning (ML)-based fault detection and classification
approach in induction motors, investigating the impact of various data preparation and …

In this work, the authors identified opportunities for improvements in conversational systems.
In order to solve the conversational systems learning problems, this investigation proposes a …