This paper describes unsupervised speech/speaker cluster validity measures based on a dissimilarity metric, for the purpose of estimating the number of clusters in a speech data s...
Kuntoro Adi, Kristine E. Sonstrom, Peter M. Scheif...
In this paper, a similarity-driven cluster merging method is proposed for unsupervised fuzzy clustering. The cluster merging method is used to resolve the problem of cluster valid...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Since clustering is unsupervised and highly explorative, clustering validation (i.e. assessing the quality of clustering solutions) has been an important and long standing researc...
Recently, performance prediction has been successfully applied in the field of information retrieval for content analysis and retrieval tasks. This paper discusses how performance ...