Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...
Abstract. Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can ...
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
We consider the problem of dealing with irrelevant votes when a multi-case classifier is built from an ensemble of binary classifiers. We show how run-off elections can be used to...
Non-stationary signal classification is a complex problem. This problem becomes even more difficult if we add the following hypothesis: each signal includes a discriminant wavefor...