pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
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Download Latest Version (.zip)- bug_report.md
- python-package.yml
- Benchmark_1_Distributions.ipynb
- Benchmark_2_General_Mixture_Models.ipynb
- Benchmark_3_KMeans.ipynb
- Benchmark_4_Bayes_Classifier.ipynb
- Benchmark_5_Hidden_Markov_Model.ipynb
- custom.css
- class.rst
- pomegranate-logo.png
- pomegranate_comparison.png
- B_Model_Tutorial_1_Distributions.ipynb
- B_Model_Tutorial_2_General_Mixture_Models.ipynb
- B_Model_Tutorial_3_Bayes_Classifier.ipynb
- B_Model_Tutorial_4_Hidden_Markov_Models.ipynb
- B_Model_Tutorial_5_Markov_Chains.ipynb
- B_Model_Tutorial_6_Bayesian_Networks.ipynb
- B_Model_Tutorial_7_Factor_Graphs.ipynb
- C_Feature_Tutorial_1_GPU_Usage.ipynb
- C_Feature_Tutorial_2_Mixed_Precision_and_DataTypes.ipynb
- C_Feature_Tutorial_3_Out_Of_Core_Learning.ipynb
- C_Feature_Tutorial_4_Priors_and_Semi-supervised_Learning.ipynb
- api.rst
- CODE_OF_CONDUCT.rst
- conf.py
- faq.rst
- index.rst
- install.rst
- Makefile
- requirements.txt
- whats_new.rst
- Bayesian_Network_Monty_Hall.ipynb
- __init__.py
- _distribution.py
- bernoulli.py
- categorical.py
- conditional_categorical.py
- dirac_delta.py
- exponential.py
- gamma.py
- halfnormal.py
- independent_components.py
- joint_categorical.py
- lognormal.py
- normal.py
- poisson.py
- student_t.py
- uniform.py
- zero_inflated.py
- __init__.py
- _base.py
- dense_hmm.py
- sparse_hmm.py
- __init__.py
- _bayes.py
- _utils.py
- bayes_classifier.py
- bayesian_network.py
- factor_graph.py
- gmm.py
- kmeans.py
- markov_chain.py
- pomegranate data intelligence 2017.pdf
- pomegranate odsc east 2017 turorial.pdf
- pomegranate ODSC East 2019.pdf
- pomegranate ODSC Europe 2020.pdf
- pomegranate ODSC West 2017.pdf
- pomegranate ODSC West 2018.pdf
- pomegranate ODSC West 2019.pdf
- pomegranate PyData NYC 2017.pdf
- pomegranate pydata seattle 2017.pdf
- pomegranate scipy 2017.pdf
- __init__.py
- _utils.py
- test_bernoulli.py
- test_categorical.py
- test_conditional_categorical.py
- test_dirac_delta.py
- test_exponential.py
- test_gamma.py
- test_independent_component.py
- test_joint_categorical.py
- test_normal_diagonal.py
- test_normal_full.py
- test_poisson.py
- test_student_t.py
- test_uniform.py
- __init__.py
- test_dense_hmm.py
- test_sparse_hmm.py
- __init__.py
- test_bayes_classifier.py
- test_bayesian_network.py
- test_bayesian_network_structure_learning.py
- test_factor_graph.py
- test_gmm.py
- test_kmeans.py
- test_markov_chain.py
- test_semisupervised.py
- test_utils.py
- tools.py
- .gitignore
- .readthedocs.yaml
- LICENSE
- README.md
- requirements.txt
- setup.py
# Installation Guide
1. Get the code
git clone https://github.com/jmschrei/pomegranate
Downloads the entire project code from GitHub to your computer.
cd pomegranate
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
pip install -r requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
jupyter notebook
Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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