When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
Feature and structure selection is an important part of many classification problems. In previous papers, an approach called basis pursuit classification has been proposed which p...
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Accurate application traffic classification and identification are important for network monitoring and analysis. The accuracy of traditional Internet application traffic classific...
Byungchul Park, Young J. Won, Mi-Jung Choi, Myung-...