https://github.com/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.
https://github.com/labo-lacourse/stepmix
classification clustering expectation-maximization latent-class-analysis lca machine-learning mixture-models supervised-learning
Last synced: about 1 month ago
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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.
- Host: GitHub
- URL: https://github.com/labo-lacourse/stepmix
- Owner: Labo-Lacourse
- License: mit
- Created: 2022-01-06T16:29:31.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2025-07-14T14:56:59.000Z (9 months ago)
- Last Synced: 2025-09-06T23:16:10.563Z (7 months ago)
- Topics: classification, clustering, expectation-maximization, latent-class-analysis, lca, machine-learning, mixture-models, supervised-learning
- Language: Python
- Homepage: https://stepmix.readthedocs.io/en/latest/index.html
- Size: 482 KB
- Stars: 76
- Watchers: 8
- Forks: 6
- Open Issues: 18
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Metadata Files:
- Readme: README-dev.md
- License: LICENSE