Machine learning allows computers to learn and discern patterns without actually being
programmed. When Statistical techniques and machine learning are combined together they …

This paper presents four kernel-based algorithms for damage detection under varying
operational and environmental conditions, namely based on one-class support vector …

Epileptic seizure detection requires specialized approaches such as video/
electroencephalography monitoring. However, these approaches are restricted mainly to …

A number of important applied problems in engineering, finance and medicine can be
formulated as a problem of anomaly detection. A classical approach to the problem is to …

Twin support vector machine (TSVM) finds two nonparallel planes by solving a pair of
smaller-sized quadratic programming problems (QPPs) rather than a single large one as in …

This paper proposes a novel method for solving one-class classification problems. The
proposed approach, namely Subspace Support Vector Data Description, maps the data to a …

We present ClusterSVDD, a methodology that unifies support vector data descriptions
(SVDDs) and k-means clustering into a single formulation. This allows both methods to …

The objective of the paper is to develop a vibration-based automated procedure dealing with
early detection of mechanical degradation of helicopter drive train components using Health …

Several methods have been proposed to solve the one-class classification problem for
vectors. Three methods are mainly used: density estimation, boundary methods, and …

To meet customer expectations and remain competitive, industrials try constantly to improve
their quality control systems. There is hence increasing demand for adopting automatic …