Merge pull request #54 from eli5-org/fix-outdated-gh-links

lopuhin · web-flow · commit 17338cc83ffe · 2025-04-05T20:22:18.000+01:00
fix outdated github links
diff --git a/README.rst b/README.rst
@@ -73,7 +73,7 @@ and formatting on a client.
 
 .. _lightning: https://github.com/scikit-learn-contrib/lightning
 .. _scikit-learn: https://github.com/scikit-learn/scikit-learn
-.. _sklearn-crfsuite: https://github.com/TeamHG-Memex/sklearn-crfsuite
+.. _sklearn-crfsuite: https://github.com/scrapinghub/sklearn-crfsuite
 .. _LIME: https://eli5.readthedocs.io/en/latest/blackbox/lime.html
 .. _TextExplainer: https://eli5.readthedocs.io/en/latest/tutorials/black-box-text-classifiers.html
 .. _xgboost: https://github.com/dmlc/xgboost
diff --git a/docs/source/_notebooks/debug-sklearn-crfsuite.rst b/docs/source/_notebooks/debug-sklearn-crfsuite.rst
@@ -4,7 +4,7 @@ Named Entity Recognition using sklearn-crfsuite
 
 In this notebook we train a basic CRF model for Named Entity Recognition
 on CoNLL2002 data (following
-https://github.com/TeamHG-Memex/sklearn-crfsuite/blob/master/docs/CoNLL2002.ipynb)
+https://github.com/eli5-org/sklearn-crfsuite/blob/master/docs/CoNLL2002.ipynb)
 and check its weights to see what it learned.
 
 To follow this tutorial you need NLTK > 3.x and sklearn-crfsuite Python
diff --git a/docs/source/_notebooks/text-explainer.rst b/docs/source/_notebooks/text-explainer.rst
@@ -2059,7 +2059,7 @@ which seems to work OK for token-based explanations. But a good sampling
 strategy which works for many real-world tasks could be a research topic
 on itself. If you’ve got some experience with it we’d love to hear from
 you - please share your findings in eli5 issue tracker (
-https://github.com/TeamHG-Memex/eli5/issues )!
+https://github.com/eli5-org/eli5/issues )!
 
 Customizing TextExplainer: classifier
 -------------------------------------
diff --git a/docs/source/_notebooks/xgboost-titanic.rst b/docs/source/_notebooks/xgboost-titanic.rst
@@ -11,7 +11,7 @@ has not too many features, but is still interesting enough.
 We are using `XGBoost <https://xgboost.readthedocs.io/en/latest/>`__
 0.81 and data downloaded from https://www.kaggle.com/c/titanic/data (it
 is also bundled in the eli5 repo:
-https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/titanic-train.csv).
+https://github.com/eli5-org/eli5/blob/master/notebooks/titanic-train.csv).
 
 1. Training data
 ----------------
diff --git a/docs/source/blackbox/lime.rst b/docs/source/blackbox/lime.rst
@@ -43,7 +43,7 @@ To understand how to use ``eli5.lime`` with text data check the
 :ref:`TextExplainer tutorial <lime-tutorial>`. API reference is available
 :mod:`here <eli5.lime>`. Currently eli5 doesn't provide a lot of helpers
 for LIME + non-text data, but there is an IPyhton
-`notebook <https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/LIME%20and%20synthetic%20data.ipynb>`__
+`notebook <https://github.com/eli5-org/eli5/blob/master/notebooks/LIME%20and%20synthetic%20data.ipynb>`__
 with an example of applying LIME for such tasks.
 
 Caveats
diff --git a/docs/source/contribute.rst b/docs/source/contribute.rst
@@ -3,8 +3,8 @@ Contributing
 
 ELI5 uses MIT license; contributions are welcome!
 
-* Source code: https://github.com/TeamHG-Memex/eli5
-* Issue tracker: https://github.com/TeamHG-Memex/eli5/issues
+* Source code: https://github.com/eli5-org/eli5
+* Issue tracker: https://github.com/eli5-org/eli5/issues
 
 ELI5 supports Python 3.9+.
 To run tests make sure tox_ Python package is installed, then run
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -9,8 +9,8 @@ Welcome to ELI5's documentation!
    :target: https://github.com/eli5-org/eli5/actions
    :alt: Build Status
 
-.. image:: https://codecov.io/github/TeamHG-Memex/eli5/coverage.svg?branch=master
-   :target: https://codecov.io/github/TeamHG-Memex/eli5?branch=master
+.. image:: https://codecov.io/github/eli5-org/eli5/coverage.svg?branch=master
+   :target: https://codecov.io/github/eli5-org/eli5?branch=master
    :alt: Code Coverage
 
 ELI5_ is a Python library which allows to visualize and debug
@@ -32,4 +32,4 @@ explain black-box models.
 
 License is MIT.
 
-.. _ELI5: https://github.com/TeamHG-Memex/eli5
+.. _ELI5: https://github.com/eli5-org/eli5
diff --git a/docs/source/libraries/sklearn.rst b/docs/source/libraries/sklearn.rst
@@ -358,6 +358,6 @@ OneVsRestClassifier
 OneVsRestClassifier_ by dispatching to the explanation function for
 OvR base estimator, and then calling this function for the
 OneVsRestClassifier instance. This works in many cases, but not for all.
-Please report issues to https://github.com/TeamHG-Memex/eli5/issues.
+Please report issues to https://github.com/eli5-org/eli5/issues.
 
 .. _OneVsRestClassifier: http://scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsRestClassifier.html
diff --git a/docs/source/libraries/sklearn_crfsuite.rst b/docs/source/libraries/sklearn_crfsuite.rst
@@ -7,7 +7,7 @@ sklearn-crfsuite_ is a sequence classification library. It provides
 a higher-level API for python-crfsuite_; python-crfsuite_ is a Python binding
 for CRFSuite_ C++ library.
 
-.. _sklearn-crfsuite: https://github.com/TeamHG-Memex/sklearn-crfsuite
+.. _sklearn-crfsuite: https://github.com/scrapinghub/sklearn-crfsuite
 .. _python-crfsuite: https://github.com/scrapinghub/python-crfsuite
 .. _CRFSuite: https://github.com/chokkan/crfsuite
 
diff --git a/docs/source/overview.rst b/docs/source/overview.rst
@@ -69,8 +69,8 @@ DataFrame objects.
 
 .. _lightning: https://github.com/scikit-learn-contrib/lightning
 .. _scikit-learn: https://github.com/scikit-learn/scikit-learn
-.. _sklearn-crfsuite: https://github.com/TeamHG-Memex/sklearn-crfsuite
-.. _ELI5: https://github.com/TeamHG-Memex/eli5
+.. _sklearn-crfsuite: https://github.com/scrapinghub/sklearn-crfsuite
+.. _ELI5: https://github.com/eli5-org/eli5
 .. _xgboost: https://github.com/dmlc/xgboost
 
 
@@ -113,7 +113,7 @@ if you're using one of the scikit-learn_ vectorizers with char ngrams:
 .. image:: static/char-ngrams.png
 
 To learn more, follow the :ref:`Tutorials`, check example IPython
-`notebooks <https://github.com/TeamHG-Memex/eli5/tree/master/notebooks>`_
+`notebooks <https://github.com/eli5-org/eli5/tree/master/notebooks>`_
 and read documentation specific to your framework in the
 :ref:`supported-libraries` section.
 
diff --git a/docs/source/tutorials/black-box-text-classifiers.rst b/docs/source/tutorials/black-box-text-classifiers.rst
@@ -4,6 +4,6 @@
 
     This tutorial can be run as an IPython notebook_.
 
-.. _notebook: https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/TextExplainer.ipynb
+.. _notebook: https://github.com/eli5-org/eli5/blob/master/notebooks/TextExplainer.ipynb
 
 .. include:: ../_notebooks/text-explainer.rst
diff --git a/docs/source/tutorials/keras-image-classifiers.rst b/docs/source/tutorials/keras-image-classifiers.rst
@@ -5,6 +5,6 @@
     This tutorial is intended to be run in an IPython notebook.
     It is also available as a notebook file here_.
 
-.. _here: https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/keras-image-classifiers.ipynb
+.. _here: https://github.com/eli5-org/eli5/blob/master/notebooks/keras-image-classifiers.ipynb
 
 .. include:: ../_notebooks/keras-image-classifiers.rst
diff --git a/docs/source/tutorials/sklearn-text.rst b/docs/source/tutorials/sklearn-text.rst
@@ -5,6 +5,6 @@
     This tutorial is intended to be run in an IPython notebook.
     It is also available as a notebook file here_.
 
-.. _here: https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/Debugging%20scikit-learn%20text%20classification%20pipeline.ipynb
+.. _here: https://github.com/eli5-org/eli5/blob/master/notebooks/Debugging%20scikit-learn%20text%20classification%20pipeline.ipynb
 
 .. include:: ../_notebooks/debug-sklearn-text.rst
diff --git a/docs/source/tutorials/sklearn_crfsuite.rst b/docs/source/tutorials/sklearn_crfsuite.rst
@@ -4,6 +4,6 @@
 
     This tutorial can be run as an IPython notebook_.
 
-.. _notebook: https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/sklearn-crfsuite.ipynb
+.. _notebook: https://github.com/eli5-org/eli5/blob/master/notebooks/sklearn-crfsuite.ipynb
 
 .. include:: ../_notebooks/debug-sklearn-crfsuite.rst
diff --git a/docs/source/tutorials/xgboost-titanic.rst b/docs/source/tutorials/xgboost-titanic.rst
@@ -5,6 +5,6 @@
     This tutorial is intended to be run in an IPython notebook.
     It is also available as a notebook file here_.
 
-.. _here: https://github.com/TeamHG-Memex/eli5/blob/master/notebooks/xboost-titanic.ipynb
+.. _here: https://github.com/eli5-org/eli5/blob/master/notebooks/xboost-titanic.ipynb
 
 .. include:: ../_notebooks/xgboost-titanic.rst
