We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
Abstract In this paper, an efficient K-medians clustering (unsupervised) algorithm for prototype selection and Supervised K-medians (SKM) classification technique for protein seque...
P. A. Vijaya, M. Narasimha Murty, D. K. Subramania...
For many applied problems in the context of clustering via mixture models, the estimates of the component means and covariance matrices can be affected by observations that are at...
Abstract. As the amount of information and communication increases dramatically new working environments must provide efficient mechanisms to maximize the benefits of these develop...
Albrecht Schmidt, Alexander Specker, Gerhard Parts...
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...