Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Suggestion] Better description of how to implement HMM's #1084

Open
kaare-mikkelsen opened this issue Mar 12, 2024 · 1 comment
Open

[Suggestion] Better description of how to implement HMM's #1084

kaare-mikkelsen opened this issue Mar 12, 2024 · 1 comment

Comments

@kaare-mikkelsen
Copy link

Would it be possible to better explain how to implement HMM's using pomegranate? A common treatment of HMM's deals with transition probabilities and emission probability (see, e.g, Bishop: https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf), not 'edges'. It's not readily apparent how to translate between the two pictures.

@jmschrei
Copy link
Owner

Howdy. When you have a dense transition matrix you can pass that in to edges. See the section "Dense and Sparse HMMs": https://github.com/jmschrei/pomegranate/blob/master/docs/tutorials/B_Model_Tutorial_4_Hidden_Markov_Models.ipynb

Is that not sufficient?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants