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 hyperparameters in support vector regression (SVR) determine the effectiveness of the
support vectors with fitting and predictions. However, the choice of these hyperparameters …

Abstract Support Vector Machine (SVM) and its variants are gaining momentum among the
Machine Learning community. In this paper, we present a quantitative analysis between the …

Twin support vector machines (TWSVM) is a new machine learning method based on the
theory of Support Vector Machine (SVM). Unlike SVM, TWSVM would generate two non …

In this paper, we propose two efficient approaches of twin support vector machines
(TWSVM). The first approach is to reformulate the TWSVM formulation by introducing L_1 L …

In this paper, we propose a novel classifier termed as twin-parametric margin support vector
machine with truncated pinball loss (TPin-TSVM), which is motivated by the twin-parametric …

Early diagnosis and treatment are the most important strategies to prevent deaths from
several diseases. In this regard, data mining and machine learning techniques have been …

The least squares twin support vector machine (LSTSVM) generates two non-parallel
hyperplanes by directly solving a pair of linear equations as opposed to solving two …

In general, introducing robust distance metrics and loss functions in the learning process
can improve the robustness of the algorithms. In this work, we first propose a new robust loss …