Clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. This paper proposes a new graph-b...
— A piecewise linear network is discussed which classifies N-dimensional input vectors. The network uses a distance measure to assign incoming input vectors to an appropriate clu...
A. A. Abdurrab, Michael T. Manry, Jiang Li, Sanjee...
Abstract. This paper proposes a new knowledge-based method for clustering metagenome short reads. The method incorporates biological knowledge in the clustering process, by means o...
Gianluigi Folino, Fabio Gori, Mike S. M. Jetten, E...
— This paper proposes an algorithm to deal with the feature selection in Gaussian mixture clustering by an iterative way: the algorithm iterates between the clustering and the un...
Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single...