depscope
Packages
IntegrateAPI DocsCuratorBenchmarkCoverage
Sign inGet API access
depscope/conda/r-bgmm

r-bgmm

condav1.8.5

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>.

License GPL-3.0-only3 versions1 maintainers0 deps289 weekly dl
49
/ 100
Health
use with caution

[email protected] low health (49/100) — consider alternatives

  • Moderate health score (49/100) — verify manually
Health breakdown0 – 100
10/25
maintenance
3/20
popularity
25/25
security
9/15
maturity
2/15
community
Vulnerabilities
0
none known

Health History

Dependency Tree

License Audit

API access

Get this data programmatically — free, no authentication.

curl https://depscope.dev/api/check/conda/r-bgmm

First published · 2021-05-28 03:17:40.877000+00:00

Last updated · 2025-09-18 07:16:06.604000+00:00

DepScope

Package intelligence for AI agents. 19 ecosystems.

Resources
API DocumentationHallucination BenchmarkFor EnterpriseSwagger / OpenAPIPopular PackagesCoverageAI Plugin SetupWatch the pitch (60s)
Legal
Legal hubPrivacy PolicyTerms of ServiceCookie PolicyAcceptable UseAttributionDPASub-processorsSecurityImprintContact中文
© 2026 Cuttalo srl — Italy · VAT IT03242390734Built for AI agents