Interesting resources related to XAI (Explainable Artificial Intelligence)
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May 31, 2022 - R
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interpretability
Here are 30 public repositories matching this topic...
📍 Interactive Studio for Explanatory Model Analysis
visualization learning r ai interactive model machine human interactivity interpretability explainable-ai xai model-visualization interpretable interpretable-machine-learning iml explainable explanatory-model-analysis explainable-machine-learning
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Aug 31, 2023 - R
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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May 13, 2026 - R
Model Agnostics breakDown plots
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Mar 12, 2024 - R
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
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Nov 30, 2023 - R
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
machine-learning human-in-the-loop interpretability explainable-artificial-intelligence researchers interactive-machine-learning deep-learning-visualization human-in-the-loop-machine-learning explainable-ml xai interpretable interpretable-machine-learning iml model-interpretability explainable interpretable-models explainable-models interpretable-learning explaining-ai explanation-methods
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Sep 29, 2022 - R
Different SHAP algorithms
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Sep 20, 2025 - R
Friedman's H-statistics
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Jan 1, 2026 - R
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
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Aug 21, 2019 - R
Data generator for Arena - interactive XAI dashboard
ema interpretability xai iml explainability explanatory-model-analysis axplainable-artificial-intelligence interactive-xai
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Sep 30, 2020 - R
Surrogate Assisted Feature Extraction in R
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Aug 13, 2022 - R
Machine learning explanations
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Oct 13, 2025 - R
ExplaineR is an R package built for enhanced interpretation of classification and regression models based on SHAP method and interactive visualizations with unique functionalities so please feel free to check it out, See ExplaineR paper at doi:10.1093/bioadv/vbae049
machine-learning cran statistics ai regression classification machine-learning-pipelines clinical-research interpretability explainable-ai shap explainability ai-pipeline ml-tools ai-tools
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Aug 17, 2025 - R
Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression discontinuity designs)
machine-learning r statistics causal-inference bayesian-statistics interpretability instrumental-variable interpretable-machine-learning fuzzy-rdd
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Mar 6, 2024 - R
Decision tree interpreter for randomForest/ranger as described in
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Sep 18, 2025 - R
BSTVC-R is an R package for spatiotemporal heterogeneous analysis within a unified full-map framework. It supports the analysis of locally varying influencing factors, identification of key global drivers, and dynamic prediction, providing a programmable and reproducible workflow for spatiotemporal interpretable modeling.
r r-package spatial-statistics interpretability geoai spatiotemporal-data-analysis baysian-models spatiotemporal-modeling
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Sep 28, 2026 - R
An R package providing functions for interpreting and distilling machine learning models
machine-learning random-forest model xgboost bart interpretability explainable-ml interpretable-machine-learning explainable-machine-learning distillation-model
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Apr 19, 2023 - R
"The Importance of being Ernest, Ekundayo, or Eswari: An Interpretable Machine Learning Approach to Name-based Ethnicity Classification" Authors: Vaishali Jain, Ted Enamorado, and Cynthia Rudin
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Jan 6, 2023 - R
Explainable Boosting Machines
machine-learning ai blackbox interpretability interpretable-ai interpretable-ml explainable-ai explainable-ml xai interpretable interpretable-machine-learning iml glassbox interpretable-models explainable-machine-learning interpretability-and-explainability
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Mar 6, 2025 - R
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