Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …

At present, the excellent performance of support vector machine (SVM) has made it
successfully applied in many fields. However, when SVM is used for two-dimensional matrix …

In most of the real world datasets, there is an imbalance in the number of samples belonging
to different classes. Various pattern classification problems such as fault or disease …

In real world problems, imbalance of data samples poses major challenge for the
classification problems as the data samples of a particular class are dominating. Problems …

Cardiovascular disease (CVD) makes our heart and blood vessels dysfunctional and often
leads to death or physical paralysis. Therefore, early and automatic detection of CVD can …

Support vector machine (SVM) is widely recognized as an effective classification tool and
has demonstrated superior performance in diverse applications. However, for large-scale …

Anomaly detection defines as a problem of finding those data samples, which do not follow
the patterns of the majority of data points. Among the variety of methods and algorithms …

Intuitionistic fuzzy (IF) set theory combined with twin support vector machines (TSVM) has
shown highly advantageous performance in robust and fast classification. However, the …

Studies on the traditional support vector machine (SVM) implicitly assume that the costs of
different types of mistakes are the same and minimize the error rate. On the one hand, it is …

In this paper, we propose a robust smooth pinball loss nonparallel support vector machine
(SpinNSVM) for binary classification. We first define a smooth pinball loss function, which is …