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| Name: python3-pomegranate-devel | Distribution: SUSE Linux Enterprise 15 SP3 |
| Version: 0.12.0 | Vendor: openSUSE |
| Release: bp153.1.18 | Build date: Sun Mar 7 02:16:08 2021 |
| Group: Unspecified | Build host: obs-arm-8 |
| Size: 23733504 | Source RPM: python-pomegranate-0.12.0-bp153.1.18.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://github.com/jmschrei/pomegranate | |
| Summary: Development files for python3-pomegranate | |
Pomegranate is a graphical models library for Python, implemented in Cython for speed. This package provides development files needed to run software that depends on Pomegranate.
MIT
* Mon Jun 08 2020 Tomáš 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
/usr/lib64/python3.6/site-packages/pomegranate/BayesClassifier.c /usr/lib64/python3.6/site-packages/pomegranate/BayesianNetwork.c /usr/lib64/python3.6/site-packages/pomegranate/FactorGraph.c /usr/lib64/python3.6/site-packages/pomegranate/MarkovChain.c /usr/lib64/python3.6/site-packages/pomegranate/MarkovNetwork.c /usr/lib64/python3.6/site-packages/pomegranate/NaiveBayes.c /usr/lib64/python3.6/site-packages/pomegranate/base.c /usr/lib64/python3.6/site-packages/pomegranate/bayes.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/BernoulliDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/BetaDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/ConditionalProbabilityTable.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/DirichletDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/DiscreteDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/ExponentialDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/GammaDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/IndependentComponentsDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/JointProbabilityTable.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/KernelDensities.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/LogNormalDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/MultivariateGaussianDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/NormalDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/PoissonDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/UniformDistribution.c /usr/lib64/python3.6/site-packages/pomegranate/distributions/distributions.c /usr/lib64/python3.6/site-packages/pomegranate/gmm.c /usr/lib64/python3.6/site-packages/pomegranate/hmm.c /usr/lib64/python3.6/site-packages/pomegranate/kmeans.c /usr/lib64/python3.6/site-packages/pomegranate/parallel.c /usr/lib64/python3.6/site-packages/pomegranate/utils.c /usr/share/licenses/python3-pomegranate-devel /usr/share/licenses/python3-pomegranate-devel/LICENSE
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