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#

shap

Here are 702 public repositories matching this topic...

A game theoretic approach to explain the output of any machine learning model.

  • UpdatedNov 4, 2025
  • Jupyter Notebook

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

  • UpdatedOct 3, 2025
  • Jupyter Notebook

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

  • UpdatedAug 1, 2025
  • Python
shapiq

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

  • UpdatedJun 8, 2024
  • Jupyter Notebook

Fast SHAP value computation for interpreting tree-based models

  • UpdatedJun 26, 2023
  • Python

利用lightgbm做(learning to rank)排序学习,包括数据处理、模型训练、模型决策可视化、模型可解释性以及预测等。Use LightGBM to learn ranking, including data processing, model training, model decision visualization, model interpretability and prediction, etc.

  • UpdatedSep 11, 2022
  • Python

A power-full Shapley feature selection method.

  • UpdatedOct 7, 2025
  • Python

TimeSHAP explains Recurrent Neural Network predictions.

  • UpdatedDec 21, 2023
  • Jupyter Notebook

SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.

  • UpdatedApr 19, 2025
  • Python
awesome-shapley-valuesurvexShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

  • UpdatedMay 6, 2024
  • Julia

streamlit-shap provides a wrapper to display SHAP plots in Streamlit.

  • UpdatedJul 21, 2022
  • Python
Fooling-LIME-SHAP

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

  • UpdatedDec 8, 2022
  • Jupyter Notebook
shapFlex

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

  • UpdatedJun 9, 2020
  • R

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