Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly
emerging efficient machine learning techniques which offer promising solutions for …

Twin support vector machines (TWSVM), a novel machine learning algorithm developing
from traditional support vector machines (SVM), is one of the typical nonparallel support …

The learning problem from imbalanced data sets poses a major challenge in data mining
community. Although conventional support vector machine can generally show relatively …

Abstract Least Squares Twin Support Vector Machine (LST-SVM) has been shown to be an
efficient and fast algorithm for binary classification. In many real-world applications, samples …

Twin support vector machine (TSVM) is an effective machine learning tool for classification
problems. However, TSVM classifier works on empirical risk principle only and also while …

The recently proposed twin support vector clustering (TWSVC) is a powerful clustering
method. However, TWSVC may encounter the singularity problem and it is time consuming …

Analyzing unlabeled data is of prime importance in machine learning. Creating groups and
identifying an underlying clustering principle is essential to many fields, such as biomedical …

Ramp-based twin support vector clustering (RampTWSVC) is a powerful clustering method,
which measures the within-cluster and between-cluster scatter by the bounded ramp …

Clustering is a widely used machine learning technique for unlabelled data. One of the
recently proposed techniques is the twin support vector clustering (TWSVC) algorithm. The …

Clustering is a prominent unsupervised learning technique. In the literature, many plane
based clustering algorithms are proposed, such as the twin support vector clustering …