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REORG tutorials
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jmschrei committed Apr 16, 2023
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5 changes: 4 additions & 1 deletion .readthedocs.yaml
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Expand Up @@ -20,4 +20,7 @@ sphinx:
# Optionally declare the Python requirements required to build your docs
python:
install:
- requirements: docs/requirements.txt
- requirements: docs/requirements.txt
- name: install dependencies
run: |
conda install pandoc
35 changes: 35 additions & 0 deletions docs/api.rst
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Expand Up @@ -57,3 +57,38 @@ This returns the matrix of posterior probabilities P(M|D) directly. The predict
>>> model.predict_log_proba(X)
This returns the matrix of log posterior probabilities for numerical stability.


API Reference
-------------

.. automodule:: pomegranate.distributions
:members: Bernoulli, Categorical, ConditionalCategorical, JointCategorical, DiracDelta, Exponential, Gamma, Normal, Poisson, StudentT, Uniform, ZeroInflated

.. automodule:: pomegranate.bayes_classifier.BayesClassifier
:members:
:inherited-members:

.. automodule:: pomegranate.gmm.GeneralMixtureModel
:members:
:inherited-members:

.. automodule:: pomegranate.hmm.DenseHMM
:members:
:inherited-members:

.. automodule:: pomegranate.hmm.SparseHMM
:members:
:inherited-members:

.. automodule:: pomegranate.markov_chain.MarkovChain
:members:
:inherited-members:

.. automodule:: pomegranate.bayesian_network.BayesianNetwork
:members:
:inherited-members:

.. automodule:: pomegranate.factor_graph.FactorGraph
:members:
:inherited-members:
4 changes: 0 additions & 4 deletions docs/conf.py
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html_theme = 'sphinx_rtd_theme'
html_static_path = ['_static']
html_css_files = ['custom.css']

html_theme_options = {
"linkcolor": "red"
}
37 changes: 0 additions & 37 deletions docs/features/nan.rst

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33 changes: 0 additions & 33 deletions docs/features/ooc.rst

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49 changes: 0 additions & 49 deletions docs/features/semisupervised.rst

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21 changes: 11 additions & 10 deletions docs/index.rst
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Expand Up @@ -50,19 +50,20 @@ Contributions are eagerly accepted! If you would like to contribute a feature th
:hidden:
:caption: Features

features/ooc.rst
features/semisupervised.rst
features/nan.rst
tutorials/C_Feature_Tutorial_1_GPU_Usage.ipynb
tutorials/C_Feature_Tutorial_2_Mixed_Precision_and_DataTypes.ipynb
tutorials/C_Feature_Tutorial_3_Out_Of_Core_Learning.ipynb
tutorials/C_Feature_Tutorial_4_Priors_and_Semi-supervised_Learning.ipynb

.. toctree::
:maxdepth: 1
:hidden:
:caption: Models

models/distributions.rst
models/gmm.rst
models/bayes_classifier.rst
models/hmm.rst
models/markov_chain.rst
models/bayesian_network.rst
models/factor_graph.rst
tutorials/B_Model_Tutorial_1_Distributions.ipynb
tutorials/B_Model_Tutorial_2_General_Mixture_Models.ipynb
tutorials/B_Model_Tutorial_3_Bayes_Classifier.ipynb
tutorials/B_Model_Tutorial_4_Hidden_Markov_Models.ipynb
tutorials/B_Model_Tutorial_5_Markov_Chains.ipynb
tutorials/B_Model_Tutorial_6_Bayesian_Networks.ipynb
tutorials/B_Model_Tutorial_7_Factor_Graphs.ipynb

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