diff --git a/README.rst b/README.rst index ecd53a6c..db223171 100644 --- 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 index 7a41e6e0..fe62bf6a 100644 --- 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 index b8aa91e4..18c70e15 100644 --- 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 index d16781b9..1629b9fb 100644 --- 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 `__ 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 index 5c5af44e..2accda0a 100644 --- 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 `. API reference is available :mod:`here `. Currently eli5 doesn't provide a lot of helpers for LIME + non-text data, but there is an IPyhton -`notebook `__ +`notebook `__ with an example of applying LIME for such tasks. Caveats diff --git a/docs/source/contribute.rst b/docs/source/contribute.rst index 512217a9..edfb1b33 100644 --- 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 index 97c5445c..49cbd2ab 100644 --- 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 index d05be37a..01547040 100644 --- 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 index d7b21b11..a58437cc 100644 --- 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 index b8fa5db5..93732628 100644 --- 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 `_ +`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 index 382977e5..c5753174 100644 --- 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 index 9e25560b..a0b65e10 100644 --- 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 index 21ea413e..2d82873f 100644 --- 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 index 8ec06bee..2384c2b6 100644 --- 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 index 63bf3144..bda35f6c 100644 --- 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