7 Major problems exist in both crisp and fuzzy clustering algorithms. The fuzzy c-means type of algorithms use weights determined by a power m of inverse distances that remains
Abstract: Since nodes in a sensor network have limited energy, prolonging the network lifetime and improving scalability become important. In this paper, we propose a distributed w...
We propose a method for supporting query refinement using topical term clusters. First, we propose a new term weighting method that can extract terms strongly related to a specifi...
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 ...
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...