bgmm
Gaussian Mixture Modeling Algorithms and the Belief-Based Mixture Modeling
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>.
- Version1.8.5
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- bgmm citation info
- Last release10/10/2021
Documentation
Team
Przemyslaw Biecek
MaintainerShow author detailsEwa Szczurek
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Last 30 days
This package has been downloaded 345 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.
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Last 365 days
This package has been downloaded 4,634 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Aug 22, 2024 with 48 downloads.
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Dependencies
- Depends4 packages
- Suggests1 package
- Reverse Imports1 package