Data clustering is an important task in many disciplines. A large number of studies have attempted to improve clustering by using the side information that is often encoded as pai...
We bring two rough-set-based clustering algorithms into the framework of partially supervised clustering. A mechanism of partial supervision relying on either qualitative or quanti...
—We apply a simple clustering algorithm to a large dataset of cellular telecommunication records, reducing the complexity of mobile phone users’ full trajectories and allowing ...
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
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 ...