The error-correcting output coding (ECOC) method reduces the multiclass learning problem into a series of binary classifiers. In this paper, we consider the dense ECOC methods, co...
Aijun Zhang, Zhi-Li Wu, Chun Hung Li, Kai-Tai Fang
Abstract. The support vector machine is basically to deal with a two-class classification problem. To get M-class classifiers for face recognition, it is common to construct a set ...
In this article, we present a system for the recognition of on-line handwritten mathematical formulas which is used in the electronic chalkboard (E-chalk), a multimedia system for...
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
This paper investigates the suitability of linear genetic programming (LGP) technique to model efficient intrusion detection systems, while comparing its performance with artificia...
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Support Vector Machines (SVM) have been extensively studied and have shown remarkable success in many applications. However the success of SVM is very limited when it is applied to...
In this poster we present an overview of the techniques we used to develop and evaluate a text categorisation system for the PRINCIP project which sets out to automatically classi...
Abstract. This paper proposes a new method for personal identity verification based the analysis of face images applying One Class Support Vector Machines. This is a recently intr...
Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identifica...