The class imbalance problem is one of the main challenges that hinders classifiers from
identifying unknown instances. When class distribution imbalance and class overlap coexist …

Multi-view data, stemming from diverse information sources, often suffer from
incompleteness due to various factors such as equipment failure and data transmission …

Collaborative representation-based classifiers (CRCs) have demonstrated remarkable
classification performance in various pattern recognition fields. However, their success …

The lithology log, an integral component of the master log, graphically portrays the
encountered lithological sequence during drilling operations. In addition to offering real-time …

Multiview learning (MvL) is an advancing domain in machine learning, leveraging multiple
data perspectives to enhance model performance through view-consistency and view …

Extreme risk in stock markets poses significant challenges, necessitating greater attention in
related research. This study presents an effective machine-learning model for forecasting …

Context In the software defect datasets, the number of defective instances is significantly
lower than that of non-defective instances. This imbalance adversely impacts the predictive …

Multi-view learning seeks to leverage the advantages of various views to complement each
other and make full use of the latent information in the data. Nevertheless, effectively …

In real-world applications, regression performance is significantly impeded by complex
noise. The choice of loss function is pivotal in building robust regression models, which …

Knowledge discovery is an ongoing research endeavor aimed at uncovering valuable
insights and patterns from large volumes of data in massive social systems (MSSs) …