Labo-Lacourse / stepmix

A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.

Date Created 2022-01-06 (3 years ago)

Commits 434 (last one 5 months ago)

Stargazers 67 (0 this week)

Watchers 5 (0 this week)

Forks 4

License mit

Ranking

RepositoryStats indexes 632,768 repositories, of these Labo-Lacourse/stepmix is ranked #403,420 (36th percentile) for total stargazers, and #323,896 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #77,951/129,079.

Labo-Lacourse/stepmix is also tagged with popular topics, for these it's ranked: machine-learning (#6,033/8405), classification (#395/573), clustering (#277/378)

Other Information

Labo-Lacourse/stepmix has Github issues enabled, there are 15 open issues and 43 closed issues.

There have been 11 releases, the latest one was published on 2024-02-15 (about a year ago)

Homepage URL: https://stepmix.readthedocs.io/en/latest/index.html

All Topics

lca clustering classification mixture-models machine-learning supervised-learning latent-class-analysis expectation-maximization

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434 commits on the default branch (master) since jan '22

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updated: 2025-03-12 @ 08:06pm, id: 445236976 / R_kgDOGonG8A