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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
Implementation of the Anchors algorithm: Explain black-box ML models
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Nov 21, 2019 - R
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
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Jun 9, 2020 - R
Variable importance via oscillations
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Sep 26, 2020 - R
Data generator for Arena - interactive XAI dashboard
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Sep 30, 2020 - R
Surrogate Assisted Feature Extraction in R
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Aug 13, 2022 - R
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
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Sep 29, 2022 - R
📍 Interactive Studio for Explanatory Model Analysis
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Aug 31, 2023 - R
Application of predictive models on a real data set of the obstetric medicine field and methods of interpretability on the previously fitted XGBoost model.
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Oct 15, 2023 - R
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
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Nov 30, 2023 - R
Model Agnostics breakDown plots
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Mar 12, 2024 - R
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
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May 16, 2024 - R
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