We consider clustering as computation of a structure of proximity relationships within a data set in a feature space or its subspaces. We propose a data structure to represent suc...
We have explored in this paper a framework to test in a quantitative manner the stability of different endmember extraction and spectral unmixing algorithms based on the concept o...
Fermin Ayuso, Javier Setoain, Manuel Prieto, Chris...
There are lots of validation indexes and techniques to study clustering results. Biclustering algorithms have been applied in Systems Biology, principally in DNA Microarray analysi...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Typical clustering algorithms output a single clustering of the data. However, in real world applications, data can often be interpreted in many different ways; data can have diff...