This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suit...
Serum profiling using mass spectrometry is an emerging technology with a great potential to provide biomarkers for complex diseases such as cancer. However, protein profiles obtai...
Habtom W. Ressom, Rency S. Varghese, Daniel Saha, ...
Predicting prospective healthcare costs is of increasing importance. Genetic search is used to discover attribute sets and associated posterior probability classifiers that predi...
Christopher R. Stephens, Henri Waelbroeck, S. Tall...
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...