— This paper presents a complete solution to the problem of how to parametrise cluster-based stochastic MIMO channel models from measurement data, with minimum user intervention....
Nicolai Czink, Ernst Bonek, Lassi Hentila, Jukka-P...
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
Software clustering algorithms presented in the literature rarely incorporate in the clustering process dynamic information, such as the number of function invocations during runt...
Bill Andreopoulos, Aijun An, Vassilios Tzerpos, Xi...
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
Hierarchic document clustering has been widely applied to Information Retrieval (IR) on the grounds of its potential improved effectiveness over inverted file search. However, pre...
Anastasios Tombros, Robert Villa, C. J. van Rijsbe...