Interesting resources related to XAI (Explainable Artificial Intelligence)
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Updated
May 31, 2022 - R
Interesting resources related to XAI (Explainable Artificial Intelligence)
📍 Interactive Studio for Explanatory Model Analysis
Model Agnostics breakDown plots
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
Efficient R implementation of SHAP
Data generator for Arena - interactive XAI dashboard
Surrogate Assisted Feature Extraction in R
Friedman's H-statistics
Machine learning explanations
Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression discontinuity designs)
Decision tree interpreter for randomForest/ranger as described in
An R package providing functions for interpreting and distilling machine learning models
Coefeasy is an R package under development for making regression coefficients more accessible. With this tool, you can read and report key coefficients instantly.
Reliable interpretability of biology-inspired deep neural networks
A visualization tool that explains the results of classification problems. Implemented in R and python
IILasso: Independently Interpretable Lasso
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