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r-bgmm

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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 <doi:10.18637/jss.v047.i03>.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-bgmm

Usage Tracking

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Downloads (Last 6 months): 0

About

Summary

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 <doi:10.18637/jss.v047.i03>.

Last Updated

Oct 10, 2021 at 18:33

License

GPL-3.0-only

Total Downloads

72.0K

Version Downloads

15.9K

Supported Platforms

noarch

Unsupported Platforms

linux-64 Last supported version: 1.8.3
macOS-64 Last supported version: 1.8.3
win-64 Last supported version: 1.8.3