[Scikit-learn-general] pomegranate v0.4.0 released

[Jacob Schreiber]

Hello all!

I've just released a new version of pomegranate, which is a probabilistic
modelling package for Python with a speedy cython implementation. It
currently supports the following:

* a wide range of probability distributions
* general mixture models
* hidden markov models
* naive bayes
* markov chains
* discrete bayesian networks
* factor graphs
* finite state machines

It currently outperforms other population implementations in terms of
training time, such as hmmlearn for hmms and scikit-learn for GMM and Naive
Bayes.

Please see my full post here:
https://www.reddit.com/r/Python/comments/4cllym/pomegranate_v040_fast_and_flexible_probabilistic/

and let me know if you have any questions of comments! I'd love any
feedback you have.

[Sebastian Raschka]

Oh, that looks like an awesome package, thanks for sharing!

PS: Just noticed that there's a little problem on the readthedocs page, the Edit on GitHub button links to https://github.com/jmschrei/pomegranate/blob/master/docs/source/index.rst which doesn't exist.

Post by Jacob Schreiber
Hello all!
* a wide range of probability distributions
* general mixture models
* hidden markov models
* naive bayes
* markov chains
* discrete bayesian networks
* factor graphs
* finite state machines
It currently outperforms other population implementations in terms of training time, such as hmmlearn for hmms and scikit-learn for GMM and Naive Bayes.
Please see my full post here: https://www.reddit.com/r/Python/comments/4cllym/pomegranate_v040_fast_and_flexible_probabilistic/ <https://www.reddit.com/r/Python/comments/4cllym/pomegranate_v040_fast_and_flexible_probabilistic/>
and let me know if you have any questions of comments! I'd love any feedback you have.
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