Two partially supervised mixture modeling methods:
soft-label and belief-based modeling are implemented.
For completeness, we equipped the package also with the
functionality of unsupervised, semi- and fully supervised
mixture modeling. The package can be applied also to selection
of the best-fitting from a set of models with different
component numbers or constraints on their structures.
For detailed introduction see:
Przemyslaw Biecek, Ewa Szczurek, Martin Vingron, Jerzy
Tiuryn (2012), The R Package bgmm: Mixture Modeling with
Uncertain Knowledge, Journal of Statistical Software