Over the past two decades, one-class classification (OCC) becomes very popular due to its
diversified applicability in data mining and pattern recognition problems. Concerning to …

Traditional extensions of the binary support vector machine (SVM) to multiclass problems
are either heuristics or require solving a large dual optimization problem. Here, a …

This paper presents a novel multi-class classifier based on weighted one-class support
vector machines (OCSVM) operating in the clustered feature space. We show that splitting …

Q-learning (QL) is a popular reinforcement learning algorithm that is guaranteed to converge
to optimal policies in Markov decision processes. However, QL exhibits an artifact: in …

The support vector machine (SVM) has a high generalisation ability to solve binary
classification problems, but its extension to multi-class problems is still an ongoing research …

In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …

Support vector machine (SVM) was initially designed for binary classification. To extend
SVM to the multi-class scenario, a number of classification models were proposed such as …

Abstract Least Squares Twin Support Vector Machine (LSTSVM) is a binary classifier and
the extension of it to multiclass is still an ongoing research issue. In this paper, we extended …

This paper describes MSVMpack, an open source software package dedicated to our
generic model of multi-class support vector machine. All four multi-class support vector …

The problem of extracting a minimal number of data points from a large dataset, in order to
generate a support vector machine (SVM) classifier, is formulated as a concave minimization …