Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A library for debugging/inspecting machine learning classifiers and explaining their predictions
| Date | Stars |
|---|---|
| 2026-07-31 | 329 |
| 2026-08-03 | 331 |
| 2026-08-06 | 331 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
==== ELI5 ==== .. image:: https://img.shields.io/pypi/v/eli5.svg :target: https://pypi.python.org/pypi/eli5 :alt: PyPI Version .. image:: https://github.com/eli5-org/eli5/actions/workflows/python-package.yml/badge.svg?branch=master :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 :alt: Code Coverage .. image:: https://readthedocs.org/projects/eli5/badge/?version=latest :target: https://eli5.readthedocs.io/en/latest/?badge=latest :alt: Documentation ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. .. image:: https://raw.githubusercontent.com/eli5-org/eli5/refs/heads/master/docs/source/static/readme-show-prediction.png :alt: explain_prediction for text data .. image:: https://raw.githubusercontent.com/eli5-org/eli5/refs/heads/master/docs/source/static/gradcam-catdog.png :alt: explain_prediction for image data .. image:: https://raw.githubusercontent.com/eli5-org/eli5/refs/heads/master/docs/source/static/readme-show-weights.png :alt: explain_weights for text data It provides support for the following machine learning frameworks and packages: * scikit-learn_. Currently ELI5 allows to explain weights and predictions of scikit-learn linear classifiers and regressors, print decision trees as text or as SVG, show feature importances and explain predictions of decision trees and tree-based ensembles. ELI5 understands text processing utilities from scikit-learn and can highlight text data accordingly. Pipeline and FeatureUnion are supported. It also allows to debug scikit-learn pipelines which contain HashingVectorizer, by undoing hashing. * Keras_ - explain predictions of image classifiers via Grad-CAM visualizations. * xgboost_ - show feature importances and explain predictions of XGBClassifier, XGBRegressor and xgboost.Booster. * LightGBM_ - show feature importances and explain predictions of LGBMClassifier, LGBMRegressor and lightgbm.Booster. * CatBoost_ - show feature importances of CatBoostClassifier, CatBoostRegressor and catboost.CatBoost. * lightning_ - explain weights and predictions of lightning classifiers and regressors. * sklearn-crfsuite_. ELI5 allows to check weights of sklearn_crfsuite.CRF models. * OpenAI_ python client. ELI5 allows to explain LLM predictions with token probabilities. ELI5 also implements several algorithms for inspecting black-box models (see `Inspecting Black-Box Estimators`_): * TextExplainer_ allows to explain predictions of any text classifier using LIME_ algorithm (Ribeiro et al., 2016). There are utilities for using LIME with non-text data and arbitrary black-box classifiers as well, but this feature is currently experimental. * `Permutation importance`_ method can be used to compute feature importances for black box estimators. Explanation and formatting are separated; you can get text-based explanation to display in console, HTML version embeddable in an IPython notebook or web dashboards, a ``pandas.DataFrame`` object if you want to process results further, or JSON version which allows to implement custom rendering 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/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 .. _LightGBM: https://github.com/Microsoft/LightGBM .. _Catboost: https://github.com/catboost/catboost .. _Keras: https://keras.io/ .. _Permutation importance: https://eli5.readthedocs.io/en/latest/blackbox/permutation_importance.html .. _Inspect
Excerpt of 4,374 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:90d63f156b24ae4e, llm:Description: 'A library for debugging/inspecting machine learning classifiers and explaining their predictions' (repo description).
matched fp:90d63f156b24ae4e, llm:Description: 'A library for debugging/inspecting machine learning classifiers and explaining their predictions' (repo description).
matched fp:90d63f156b24ae4e, llm:Description: 'A library for debugging/inspecting machine learning classifiers and explaining their predictions' (repo description).