Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality clas...
Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hu...
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
This paper describes a criterion for qualitative analysis of open Chemical Reaction Networks endowed with mass-action kinetics. The method can be applied to an extremely broad clas...
We present a new Bayesian approach to object identification: variants. By object identification we mean the detection of the member (regular variant) of a given statistical popula...
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...