Package Release Info

python-pomegranate-0.12.0-bp154.1.38

Update Info: Base Release
Available in Package Hub : 15 SP4

platforms

AArch64
ppc64le
s390x
x86-64

subpackages

python3-pomegranate
python3-pomegranate-devel

Change Logs

Version: 0.12.0-bp152.2.1
* Mon Jun 08 2020 Tomá? Chvátal <tchvatal@suse.com>
- Disable py2 build due to missing deps
* Mon Jan 06 2020 Todd R <toddrme2178@gmail.com>
- Update to Version 0.12.0
  + Highlights
  * MarkovNetwork models have been added in and include both inference and structure learning.
  * Support for Python 2 has been depricated.
  * Markov network, data generator, and callback tutorials have been added in
  * A robust `from_json` method has been added in to __init__.py that can deserialize JSONs from any pomegranate model.
  + MarkovNetwork
  * MarkovNetwork models have been added in as a new probabilistic model.
  * Loopy belief propagation inference has been added in using the FactorGraph backend
  * Structure learning has been added in using Chow-Liu trees
  + BayesianNetwork
  * Chow-Liu tree building has been sped up slightly, courtesy of @alexhenrie
  * Chow-Liu tree building was further sped up by almost an order of magnitude
  * Constraint Graphs no longer fail when passing in graphs with self loops, courtesy of @alexhenrie
  + BayesClassifier
  * Updated the `from_samples` method to accept BayesianNetwork as an emission. This will build one Bayesian network for each class and use them as the emissions.
  + Distributions
  * Added a warning to DiscreteDistribution when the user passes in an empty dictionary.
  * Fixed the sampling procedure for JointProbabilityTables.
  * GammaDistributions should have their shape issue resolved
  * The documentation for BetaDistributions has been updated to specify that it is a Beta-Bernoulli distribution.
  + io
  * New file added, io.py, that contains data generators that can be operated on
  * Added DataGenerator, DataFrameGenerator, and a BaseGenerator class to inherit from
  + HiddenMarkovModel
  * Added RandomState parameter to `from_samples` to account for randomness when building discrete models.
  + Misc
  * Unneccessary calls to memset have been removed, courtesy of @alexhenrie
  * Checking for missing values has been slightly refactored to be cleaner, courtesy of @mareksmid-lucid
  * Include the LICENSE file in MANIFEST.in and simplify a bit, courtesy of @toddrme2178
  * Added in a robust from_json method that can be used to deseralize a JSON for any pomegranate model.
  + docs
  * Added io.rst to briefly describe data generators
  * Added MarkovNetwork.rst to describe Markov networks
  * Added links to tutorials that did not have tutorials linked to them.
  + Tutorials
  * Added in a tutorial notebook for Markov networks
  * Added in a tutorial notebook for data generators
  * Added in a tutorial notebook for callbacks
  + CI
  * Removed unit tests for Py2.7 from AppVeyor and Travis
  * Added unit tests for Py3.8 to AppVeyor and Travis
- Dropped python2 support
* Mon Nov 18 2019 Todd R <toddrme2178@gmail.com>
- Initial version