Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
In this paper, a new, simple but effective method is proposed for blind image steganalysis, which is based on run-length histogram analysis. Higher-order statistics of characteris...
Partition testing is a well-known software testing technique. This paper shows that partition testing strategies are relatively ineffective in detecting faults related to small sh...