Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …

In the era of big data, transformation of biomedical big data into valuable knowledge has
been one of the most important challenges in bioinformatics. Deep learning has advanced …

Support vector machines (SVMs) are a supervised classifier successfully applied in a
plethora of real-life applications. However, they suffer from the important shortcomings of …

Context Ensemble methods consist of combining more than one single technique to solve
the same task. This approach was designed to overcome the weaknesses of single …

Feature selection has been considered as an effective method to solve imbalanced
classification problems. It can be formulated as a multiobjective optimization problem (MOP) …

Objectives Ameloblastomas and keratocystic odontogenic tumors (KCOTs) are important
odontogenic tumors of the jaw. While their radiological findings are similar, the behaviors of …

Long noncoding RNAs (lncRNAs) are emerging as a class of important regulators
participating in various biological functions and disease processes. With the widespread …

In the last decade, we have seen drastic changes in the air pollution level, which has
become a critical environmental issue. It should be handled carefully towards making the …

Support vector machines (SVMs) are widely employed in molecular diagnosis of disease for
their efficiency and robustness. However, there is no previous research to analyze their …

Imbalanced data problem is widely present in network intrusion detection, spam filtering,
biomedical engineering, finance, science, being a challenge in many real-life data-intensive …