iml

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

python data-science machine-learning data-mining h2o gradient-boosting-machine transparency decision-tree fairness lime accountability interpretability interpretable-ai interpretable-ml xai fatml interpretable interpretable-machine-learning iml machine-learning-interpretability

UpdatedJun 17, 2024
Jupyter Notebook

h2oai /mli-resources

Star487

H2O.ai Machine Learning Interpretability Resources

python data-science machine-learning data-mining h2o xgboost transparency jupyter-notebooks fairness accountability interpretability interpretable-ai interpretable-ml explainable-ml mli xai fatml interpretable-machine-learning iml machine-learning-interpretability

UpdatedDec 12, 2020
Jupyter Notebook

ModelOriented /modelStudio

Star331

📍 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

UpdatedAug 31, 2023
R

hbaniecki /adversarial-explainable-ai

Star312

💡 Adversarial attacks on explanations and how to defend them

security model evaluation deep adversarial defense attacks interpretability robustness adversarial-machine-learning adversarial-examples counterfactual adversarial-attacks explainable-ai xai interpretable interpretable-machine-learning iml explainability responsible-ai

UpdatedNov 30, 2024

scu-zjz /IMDLBenCo

Star120

[NeurIPS'24 Spotlight] A comprehensive benchmark & codebase for Image manipulation detection/localization.

benchmark imd image-manipulation-detection iml benco imdl imdl-benco

UpdatedMar 11, 2025
Python

The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"

scalability representation-learning nips interpretability interpretable-ai interpretable-ml explainable-ai explainable-ml xai interpretable-machine-learning iml explainability neurips interpretable-classification rule-based-model neuro-symbolic-ai

UpdatedMar 12, 2024
Python

pbiecek /breakDown

Sponsor

Star103

Model Agnostics breakDown plots

data-science machine-learning interpretability xai visual-explanations iml

UpdatedMar 12, 2024
R

nredell /ShapML.jl

Star91

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

UpdatedMay 6, 2024
Julia

ModelOriented /iBreakDown

Star84

Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)

breakdown interpretability xai shapley iml

UpdatedNov 30, 2023
R

automl /DeepCAVE

Sponsor

Star84

An interactive framework to visualize and analyze your AutoML process in real-time.

visualization real-time analysis interactive hyperparameters automl sampling-bias iml hyperparameter-importance

UpdatedMar 6, 2025
Python

ModelOriented /treeshap

Star83

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

UpdatedJul 25, 2024
R

nredell /shapFlex

Star74

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

package machine-learning r ensemble r-package causality causal-inference feature-importance causal-networks shapley interpretable-machine-learning iml shap shapley-value shapley-values

UpdatedJun 9, 2020
R

givasile /effector

Star74

Effector - a Python package for global and regional effect methods

xai iml explainability

UpdatedMar 8, 2025
Jupyter Notebook

rehmanzafar /xai-iml-sota

Star73

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

UpdatedSep 29, 2022
R

dddb11 /MVSS-Net

Star66

Unofficial implementation of MVSS-Net (ICCV 2021) with Pytorch including training code.

pytorch unofficial iml mvss-net

UpdatedSep 26, 2023
Python

ModelOriented /live

Star35

Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN

machine-learning lime interpretability xai model-visualization visual-explanations iml