Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …

In the field of early prediction of software defects, various techniques have been developed
such as data mining techniques, machine learning techniques. Still early prediction of …

Context Software defect prediction (SDP) plays an important role in allocating testing
resources reasonably, reducing testing costs, and ensuring software quality. However …

Aiming at the problem of software defect prediction difficulty caused by insufficient software
defect marker samples and unbalanced classification, a semi-supervised software defect …

Rolling bearing fault detection is of crucial significance to enhance the availability, the
reliability and the security of rotating machinery. In this paper, a novel method called …

In software fault prediction systems, there are many hindrances for detecting faulty modules,
such as missing values or samples, data redundancy, irrelevance features, and correlation …

Machine learning approaches are valuable methods in hyperspectral remote sensing,
especially for the classification of land cover or for the regression of physical parameters …

Characterizing surface water quality is important for water resources management and
protection. Numerous studies have addressed the fact that water quality is often impacted by …

When there exist not enough historical defect data for building an accurate prediction model,
semisupervised defect prediction (SSDP) and cross-project defect prediction (CPDP) are …

This paper presents an unsupervised, density-based approach to anomaly detection. The
purpose is to define a smooth yet effective measure of outlierness that can be used to detect …