Title  Choosing the number of Gaussian clusters 

Description 
Choosing the number of clusters remains a very practical challenge. We have previously discussed the problems even for kmeans (in Stop using the elbow criterion for kmeans and how to choose the number of clusters instead). But kmeans is a very simple case. Choosing the number of Gaussians for Gaussian Mixture Modeling is a closely related challenge where some of above methods (e.g., BIC) can also be used in a similar way. 
Qualification 

Proposal 
You task is to add functionality to ELKI (Java Data Mining framework) to help choosing the number of clusters for Gaussian Mixture modeling. The methods for choosing the number of clusters of these papers are to be reproduced:

Thesistype  Bachelorthesis 
Second Tutor  Schubert, Erich 
Professor  Schubert, Erich 
Status  Offen 
