A game theoretic approach to explain the output of any machine learning model.
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Jan 22, 2025 - Jupyter Notebook
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shap
Here are 384 public repositories matching this topic...
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
data-science machine-learning neural-network random-forest scikit-learn xgboost hyperparameter-optimization lightgbm ensemble feature-engineering decision-tree hyper-parameters automl automated-machine-learning catboost automatic-machine-learning mljar shap tuning-algorithm models-tuning
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Jan 14, 2025 - Python
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
python machine-learning transparency lime interpretability ethical-artificial-intelligence explainable-ml shap explainability
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Jan 10, 2025 - Jupyter Notebook
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
dashboard plotly dash data-scientists model-predictions interactive-plots interactive-dashboards xai inner-workings shap explainer xai-library shap-values permutation-importances
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Dec 29, 2024 - Python
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
feature-selection model-selection xgboost hyperparameter-optimization lightgbm parameter-tuning shap
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Jun 8, 2024 - Jupyter Notebook
Fast SHAP value computation for interpreting tree-based models
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Jun 26, 2023 - Python
Shapley Interactions and Shapley Values for Machine Learning
python machine-learning interpretability shapley shap explainability feature-interactions shapley-interactions shapiq
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Jan 22, 2025 - 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.
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Sep 11, 2022 - Python
A power-full Shapley feature selection method.
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May 3, 2024 - Python
TimeSHAP explains Recurrent Neural Network predictions.
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Dec 21, 2023 - Jupyter Notebook
Automated Tool for Optimized Modelling
visualization python data-science machine-learning scikit-learn modelling model-predictions data-exploration data-pipeline interactive-visualizations automl mlflow shap dagshub
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Jul 15, 2024 - HTML
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
data-science machine-learning deep-learning artificial-intelligence lime explainable-artificial-intelligence explainable-ai explainable-ml xai shapley shap explainability shapley-decomposition explainable shapley-value shapley-q-value shapley-additive-explanations owen-value
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Aug 8, 2022
Validation (like Recursive Feature Elimination for SHAP) of (multiclass) classifiers & regressors and data used to develop them.
data-science machine-learning statistics data-analysis tree-model multi-class-classification binary-classifiers recursive-feature-elimination shap feature-elimination regressors
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Aug 19, 2024 - Python
Explainable Machine Learning in Survival Analysis
machine-learning r variable-importance biostatistics survival-analysis r-package cox-regression cox-model time-to-event censored-data interpretable-ml explainable-ai explainable-ml xai interpretable-machine-learning brier-scores shap explanatory-model-analysis probabilistic-machine-learning explainable-machine-learning
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Jun 15, 2024 - R
A Julia package for interpretable machine learning with stochastic Shapley values
julia feature-importance shapley interpretable-machine-learning iml shap shapley-value stochastic-shapley-values
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May 6, 2024 - Julia
SHAP Plots in R
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Jan 19, 2025 - R
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
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Jul 21, 2022 - Python
SurvSHAP(t): Time-dependent explanations of machine learning survival models
learning model machine variable-importance biostatistics survival-analysis machinelearning survival cox-regression cox-model time-to-event explainable-ai xai interpretable cph brier-scores shap explainable censored probabilistic-machine-learning
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Jan 4, 2024 - Jupyter Notebook
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
machine-learning interpretability explainable-artificial-intelligence explainable-ai xai interpretable-machine-learning iml shap explainability shapley-value responsible-ml explanatory-model-analysis
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Jul 25, 2024 - R
Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
machine-learning paper lime interpretability adversarial-attacks explanations shap post-hoc-explanation fool-lime
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Dec 8, 2022 - Jupyter Notebook
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