bgmm-package: Belief-Based Gaussian Mixture Modeling

In pbiecek/bgmm: Gaussian Mixture Modeling Algorithms and the Belief-Based Mixture Modeling

Belief-Based Gaussian Mixture Modeling

Description

This package implements partially supervised mixture modeling methods: soft-label and belief-based modeling, the semi-supervised methods and for completeness also unsupervised and fully supervised methods for mixture modeling.

Details

For short overview see the webpage http://bgmm.molgen.mpg.de/rapBGMM/.

Author(s)

Przemyslaw Biecek and Ewa Szczurek

Maintainer: Przemyslaw Biecek <[e-mail]>

References

Przemyslaw Biecek, Ewa Szczurek, Martin Vingron, Jerzy Tiuryn (2012), The R Package bgmm: Mixture Modeling with Uncertain Knowledge, Journal of Statistical Software.

See Also

Package for unsupervised learning of Gaussian mixture model link{mclust}, methods for supervised learning link{MASS::lda()}, link{MASS::qda()}.

Examples

## Do not run
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#demo(bgmm)

pbiecek/bgmm documentation built on Aug. 22, 2023, 7:43 p.m.