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DOC: URLs link to original lightgbm and xgboost docs #822

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DOC: URLs link to original lightgbm and xgboost docs #822

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Dawnfz-Lenfeng Oct 9, 2024
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2 changes: 2 additions & 0 deletions doc/source/reference/index.rst
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Expand Up @@ -8,5 +8,7 @@ API Reference
:maxdepth: 2

xorbits/index
lightgbm/index
xgboost/index
datasets/index
experimental/index
29 changes: 23 additions & 6 deletions doc/source/reference/lightgbm/learning.rst
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============
Learning API
============
.. currentmodule:: xorbits.lightgbm

.. autosummary::
:toctree: generated/

predict
predict_proba
The following table lists both implemented and not implemented methods. If you have need
of an operation that is listed as not implemented, feel free to open an issue on the
`GitHub repository`_, or give a thumbs up to already created issues. Contributions are
also welcome!

The following table is structured as follows: The first column contains the method name.
The second column contains link to a description of corresponding lightgbm method.
The third column is a flag for whether or not there is an implementation in Xorbits for
the method in the left column. ``Y`` stands for yes, ``N`` stands for no, ``P`` stands
for partial (meaning some parameters may not be supported yet), and ``D`` stands for
default to lightgbm.

+----------------------+--------------+------------------------+----------------------------------+
| ``xorbits.lightgbm`` | ``lightgbm`` | Implemented? (Y/N/P/D) | Notes for Current implementation |
+----------------------+--------------+------------------------+----------------------------------+
| | | | |
+----------------------+--------------+------------------------+----------------------------------+

.. Originally, `predict` and `predict_proba methods` were included,
.. but they are not consistent with the interfaces of lightgbm.

.. _`GitHub repository`: https://github.com/xorbitsai/xorbits/issues

162 changes: 95 additions & 67 deletions doc/source/reference/lightgbm/sklearn.rst
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Scikit-Learn API
================

The following table lists both implemented and not implemented methods. If you have need
of an operation that is listed as not implemented, feel free to open an issue on the
`GitHub repository`_, or give a thumbs up to already created issues. Contributions are
also welcome!

The following table is structured as follows: The first column contains the method name.
The second column contains link to a description of corresponding lightgbm method.
The third column is a flag for whether or not there is an implementation in Xorbits for
the method in the left column. ``Y`` stands for yes, ``N`` stands for no, ``P`` stands
for partial (meaning some parameters may not be supported yet), and ``D`` stands for
default to lightgbm.

LGBMClassifier
==============
.. currentmodule:: xorbits.lightgbm

Constructor
~~~~~~~~~~~
.. autosummary::
:toctree: generated/

LGBMClassifier


Attributes
~~~~~~~~~~
.. autosummary::
:toctree: generated/

LGBMClassifier.fit
LGBMClassifier.get_params
LGBMClassifier.load_model
LGBMClassifier.predict
LGBMClassifier.predict_proba
LGBMClassifier.score
LGBMClassifier.set_params
LGBMClassifier.to_local
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``xorbits.lightgbm`` | ``lightgbm`` | Implemented? (Y/N/P/D) | Notes for Current implementation |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.fit`` | `LGBMClassifier.fit`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.get_params`` | `LGBMClassifier.get_params`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.load_model`` | `LGBMClassifier.load_model`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.predict`` | `LGBMClassifier.predict`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.predict_proba`` | `LGBMClassifier.predict_proba`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.score`` | `LGBMClassifier.score`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.set_params`` | `LGBMClassifier.set_params`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+
| ``LGBMClassifier.to_local`` | `LGBMClassifier.to_local`_ | Y | |
+----------------------------------+---------------------------------+------------------------+----------------------------------+

LGBMRegressor
=============
.. currentmodule:: xorbits.lightgbm

Constructor
~~~~~~~~~~~
.. autosummary::
:toctree: generated/

LGBMRegressor


Attributes
~~~~~~~~~~
.. autosummary::
:toctree: generated/

LGBMRegressor.fit
LGBMRegressor.get_params
LGBMRegressor.load_model
LGBMRegressor.predict
LGBMRegressor.predict_proba
LGBMRegressor.score
LGBMRegressor.set_params
LGBMRegressor.to_local
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``xorbits.lightgbm`` | ``lightgbm`` | Implemented? (Y/N/P/D) | Notes for Current implementation |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.fit`` | `LGBMRegressor.fit`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.get_params`` | `LGBMRegressor.get_params`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.load_model`` | `LGBMRegressor.load_model`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.predict`` | `LGBMRegressor.predict`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.predict_proba`` | `LGBMRegressor.predict_proba`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.score`` | `LGBMRegressor.score`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.set_params`` | `LGBMRegressor.set_params`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+
| ``LGBMRegressor.to_local`` | `LGBMRegressor.to_local`_ | Y | |
+---------------------------------+--------------------------------+------------------------+----------------------------------+

LGBMRanker
==========
.. currentmodule:: xorbits.lightgbm

Constructor
~~~~~~~~~~~
.. autosummary::
:toctree: generated/

LGBMRanker


Attributes
~~~~~~~~~~
.. autosummary::
:toctree: generated/

LGBMRanker.fit
LGBMRanker.get_params
LGBMRanker.load_model
LGBMRanker.predict
LGBMRanker.predict_proba
LGBMRanker.set_params
LGBMRanker.to_local


+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``xorbits.lightgbm`` | ``lightgbm`` | Implemented? (Y/N/P/D) | Notes for Current implementation |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.fit`` | `LGBMRanker.fit`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.get_params`` | `LGBMRanker.get_params`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.load_model`` | `LGBMRanker.load_model`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.predict`` | `LGBMRanker.predict`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.predict_proba`` | `LGBMRanker.predict_proba`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.score`` | `LGBMRanker.score`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.set_params`` | `LGBMRanker.set_params`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+
| ``LGBMRanker.to_local`` | `LGBMRanker.to_local`_ | Y | |
+------------------------------+-----------------------------+------------------------+----------------------------------+

.. _`GitHub repository`: https://github.com/xorbitsai/xorbits/issues
.. _`LGBMClassifier.fit`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.fit
.. _`LGBMClassifier.get_params` : https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.get_params
.. _`LGBMClassifier.load_model`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.load_model
.. _`LGBMClassifier.predict`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.predict
.. _`LGBMClassifier.predict_proba`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.predict_proba
.. _`LGBMClassifier.score`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.score
.. _`LGBMClassifier.set_params`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.set_params
.. _`LGBMClassifier.to_local`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html#lightgbm.LGBMClassifier.to_local
.. _`LGBMRegressor.fit`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.fit
.. _`LGBMRegressor.get_params`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.get_params
.. _`LGBMRegressor.load_model`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.load_model
.. _`LGBMRegressor.predict`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.predict
.. _`LGBMRegressor.predict_proba`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.predict_proba
.. _`LGBMRegressor.score`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.score
.. _`LGBMRegressor.set_params`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.set_params
.. _`LGBMRegressor.to_local`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html#lightgbm.LGBMRegressor.to_local
.. _`LGBMRanker.fit`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.fit
.. _`LGBMRanker.get_params`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.get_params
.. _`LGBMRanker.load_model`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.load_model
.. _`LGBMRanker.predict`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.predict
.. _`LGBMRanker.predict_proba`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.predict_proba
.. _`LGBMRanker.score`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.score
.. _`LGBMRanker.set_params`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.set_params
.. _`LGBMRanker.to_local`: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRanker.html#lightgbm.LGBMRanker.to_local
21 changes: 17 additions & 4 deletions doc/source/reference/xgboost/core.rst
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===================
Core Data Structure
===================
.. currentmodule:: xorbits.xgboost

The following table lists both implemented and not implemented methods. If you have need
of an operation that is listed as not implemented, feel free to open an issue on the
`GitHub repository`_, or give a thumbs up to already created issues. Contributions are
also welcome!

.. autosummary::
:toctree: generated/
The following table is structured as follows: The first column contains the method name.
The second column contains link to a description of corresponding xgboost method.
The third column is a flag for whether or not there is an implementation in Xorbits
for the method in the left column. ``Y`` stands for yes, ``N`` stands for no, ``P`` standsfor partial
(meaning some parameters may not be supported yet), and ``D`` stands for default to xgboost.

DMatrix
+---------------------+-------------+------------------------+----------------------------------+
| ``xorbits.xgboost`` | ``xgboost`` | Implemented? (Y/N/P/D) | Notes for Current implementation |
+---------------------+-------------+------------------------+----------------------------------+
| ``DMatrix`` | `DMatrix`_ | Y | |
+---------------------+-------------+------------------------+----------------------------------+

.. _`GitHub repository`: https://github.com/xorbitsai/xorbits/issues
.. _`DMatrix`: https://xgboost.readthedocs.io/en/latest/python/python_api.html#xgboost.DMatrix
25 changes: 20 additions & 5 deletions doc/source/reference/xgboost/learning_api.rst
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============
Learning API
============
.. currentmodule:: xorbits.xgboost

The following table lists both implemented and not implemented methods. If you have need
of an operation that is listed as not implemented, feel free to open an issue on the
`GitHub repository`_, or give a thumbs up to already created issues. Contributions are
also welcome!

.. autosummary::
:toctree: generated/
The following table is structured as follows: The first column contains the method name.
The second column contains link to a description of corresponding xgboost method.
The third column is a flag for whether or not there is an implementation in Xorbits
for the method in the left column. ``Y`` stands for yes, ``N`` stands for no, ``P`` standsfor partial
(meaning some parameters may not be supported yet), and ``D`` stands for default to xgboost.

train
predict
+---------------------+-------------+------------------------+----------------------------------+
| ``xorbits.xgboost`` | ``xgboost`` | Implemented? (Y/N/P/D) | Notes for Current implementation |
+---------------------+-------------+------------------------+----------------------------------+
| ``train`` | `train`_ | Y | |
+---------------------+-------------+------------------------+----------------------------------+

.. Originally, `predict` was included,
.. but it is not consistent with the interface of xgboost.

.. _`GitHub repository`: https://github.com/xorbitsai/xorbits/issues
.. _`train`: https://xgboost.readthedocs.io/en/latest/python/python_api.html#xgboost.train
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