Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Improving classification accuracy is a key issue to advancing brain computer interface (BCI) research from laboratory to real world applications. This article presents a high accu...
Chng Eng Siong, Cuntai Guan, Jiankang Wu, M. Thula...
Simple binary patterns have been successfully used for extracting feature representations for visual object classification. In this paper, we present a method to learn a set of d...
This paper presents a methodology for learning taxonomic relations from a set of documents that each explain one of the concepts. Three different feature extraction approaches with...