In the past recent years, Machine Learning methodologies have been applied in countless
application areas. In particular, they play a key role in enabling Industry 4.0. However, one of …

Software defect prediction (SDP) is a hot topic in the modern software engineering research
community. It has been used for evaluating software quality and reliability and allocating …

Mineral exploration targets can be delineated through multivariate analysis. These targets
are usually recognized as anomalies in the procedure of data mining using a detection …

Global crises such as the COVID-19 pandemic and other recent environmental, financial,
and economic disasters have weakened economies around the world and marginalized …

Abstract Just-In-Time (JIT) defect prediction aims to identify defects early, at commit time.
Hence, developers can take precautions to avoid defects when the code changes are still …

The cigarette detection data contains a large amount of true sample data and a small
amount of false sample data. The false sample data is regarded as abnormal data, and …

Application of the machine learning methods on strongly imbalanced datasets is a
challenging task in the field of data processing. Imbalanced learning is part of many real …

It is true that anomaly detection is an important issue that has had a long history in the
research community due to its various applications. Literature has recorded various Artificial …

[Purpose] In the research of data mining, anomaly detection algorithms can accurately find
samples of abnormal behaviors to achieve the purpose of data mining. the isolation forest …

The population of people ages 65 and older has increased since the 1960s and current
estimates indicate it will double by 2060. Medicare is a federal health insurance program for …