The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bay...
Bayesian Information Criterion (BIC) is a promising method for detecting the number of clusters. It is often used in model-based clustering in which a decisive first local maximum ...
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
In order to determine a success criterion for open-source software projects, we analyzed 122,205 projects in the SourceForge database. There were 80,597 projects with no downloads...
Dror G. Feitelson, Gillian Z. Heller, Stephen R. S...
This paper addresses the problem of unsupervised speaker change detection. Three systems based on the Bayesian Information Criterion (BIC) are tested. The first system investigat...
Margarita Kotti, Luis P. M. Martins, Emmanouil Ben...