This release is a pre-release and may not be stable for production use.
dpmmlearn is a algorithms for Dirichlet Process Mixture Model.
Dependencies
The required dependencies to use dpmmlearn are,
scikit-learn
numpy
scipy
You also need matplotlib, seaborn to run the demo and pytest to run the tests.
install
pip install dpmmlearnUSAGE
We have posted a usage example in the github’s demo folder.
License
This code is licensed under MIT License.
Test
python setup.py test1 maintainer
Metadata
1 maintainer
Release files for dpmmlearn 0.0.1b1
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| File | Size | Uploaded | Provenance | Actions |
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| dpmmlearn-0.0.1b1.tar.gz | 14.0 kB | Without provenance | Details for dpmmlearn-0.0.1b1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| dpmmlearn-0.0.1b1-py3-none-any.whl | Python 3 | none | any | Details for dpmmlearn-0.0.1b1-py3-none-any.whl |
Total release size: 28.8 kB
Release files / dpmmlearn-0.0.1b1.tar.gz
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| Size | 14.0 kB |
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Release files / dpmmlearn-0.0.1b1-py3-none-any.whl
| Download URL | dpmmlearn-0.0.1b1-py3-none-any.whl |
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| Size | 14.8 kB |
| Tags | Python 3 |
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