hmmlearn

Unsupervised learning and inference of Hidden Markov Models:

• Simple algorithms and models to learn HMMs (Hidden Markov Models) in Python,

• Follows scikit-learn API as close as possible, but adapted to sequence data,

• Built on scikit-learn, NumPy, SciPy, and Matplotlib,

• Open source, commercially usable — BSD license.

User guide: table of contents

• Tutorial
  • Available models
  • Building HMM and generating samples
  • Fixing parameters
  • Training HMM parameters and inferring the hidden states
  • Monitoring convergence
  • Working with multiple sequences
  • Saving and loading HMM
  • Implementing HMMs with custom emission probabilities
• Examples
• API Reference
  • hmmlearn.base
  • hmmlearn.hmm
  • hmmlearn.vhmm
• hmmlearn Changelog
  • Version 0.3.2
  • Version 0.3.1
  • Version 0.3.0
  • Version 0.2.8
  • Version 0.2.7
  • Version 0.2.6
  • Version 0.2.5
  • Version 0.2.4
  • Version 0.2.3
  • Version 0.2.2
  • Version 0.2.1
  • Version 0.2.0
  • Version 0.1.1