hmmlearn/hmmlearn

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3416 stars · 757 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

hmmlearn is a Python library providing algorithms for unsupervised learning and inference of Hidden Markov Models, with an API modeled on scikit-learn. It is now in limited-maintenance mode.

Use cases

• fit hidden markov models to sequence data in python
• unsupervised learning of HMM parameters
• predict hidden states for time series
• scikit-learn style API for HMMs
• model sequential data with Gaussian or categorical emissions
• segment time series into hidden regimes

When to choose

• you need HMM training and inference in Python with a familiar scikit-learn-like fit/predict API
• you want unsupervised estimation of HMM parameters from observation sequences

When to avoid

• you need supervised HMM learning (use seqlearn instead)
• you need actively developed features or rapid bug fixes, since the project is in limited-maintenance mode
• you need modern sequence models like RNNs or transformers

Facets

library · maturity maintenance

machine-learning data-science machine-learning data-science python cross-platform hidden-markov-models scikit-learn time-series unsupervised-learning sequence-modeling algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="hmmlearn/hmmlearn")