DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
☆688Feb 21, 2023Updated 3 years ago
Alternatives and similar repositories for DrWhy
Users that are interested in DrWhy are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- moDel Agnostic Language for Exploration and eXplanation☆1,490Jul 15, 2026Updated 3 months ago
- Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)☆84Nov 30, 2023Updated 2 years ago
- 📍 Interactive Studio for Explanatory Model Analysis☆333Aug 31, 2023Updated 3 years ago
- modelDown generates a website with HTML summaries for predictive models☆120Mar 25, 2026Updated 7 months ago
- Explanatory Model Analysis. Explore, Explain and Examine Predictive Models☆201Apr 14, 2024Updated 2 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Extensions for the DALEX package☆68Jan 14, 2026Updated 9 months ago
- iml: interpretable machine learning R package☆503Feb 24, 2025Updated last year
- Model verification, validation, and error analysis☆60Jan 9, 2024Updated 2 years ago
- Surrogate Assisted Feature Extraction in R☆28Aug 13, 2022Updated 4 years ago
- An R wrapper of SHAP python library☆58May 25, 2023Updated 3 years ago
- Effects and Importances of Model Ingredients☆39Mar 15, 2023Updated 3 years ago
- Flexible tool for bias detection, visualization, and mitigation☆85Oct 31, 2025Updated 11 months ago
- Data generator for Arena - interactive XAI dashboard☆30Sep 30, 2020Updated 6 years ago
- Variable importance via oscillations☆14Sep 26, 2020Updated 6 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Model Agnostics breakDown plots☆103Mar 12, 2024Updated 2 years ago
- eXtreme RuleFit (sparse linear models on XGBoost ensembles)☆44Dec 17, 2025Updated 10 months ago
- A set of tools to understand what is happening inside a Random Forest☆242Mar 25, 2024Updated 2 years ago
- Compute SHAP values for your tree-based models using the TreeSHAP algorithm☆106May 13, 2026Updated 5 months ago
- Variable Importance Plots (VIPs)☆193Jul 5, 2026Updated 3 months ago
- Fast approximate Shapley values in R☆137Jul 6, 2026Updated 3 months ago
- Trees are all you need☆112Jun 5, 2024Updated 2 years ago
- Structure mining for xgboost model☆25Jan 12, 2026Updated 9 months ago
- View and Browse Code Using Flow Diagrams☆424Updated this week
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Monitoring of AI Regulations☆19May 30, 2021Updated 5 years ago
- Run predictions inside the database☆265Oct 18, 2026Updated last week
- Analytics & Machine Learning R Sidekick☆242Oct 5, 2026Updated 3 weeks ago
- LIME-like explanations with interpretable features based on Ceteris Paribus curves. Now on CRAN.☆14Sep 19, 2021Updated 5 years ago
- 🛠️ 📊 Tools for Exploring and Comparing Data Frames☆256Jun 28, 2026Updated 4 months ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆864May 31, 2022Updated 4 years ago
- Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)☆1,162Oct 19, 2026Updated last week
- Extra recipes for predictor embeddings☆147Sep 28, 2026Updated last month
- Local Interpretable Model-Agnostic Explanations (R port of original Python package)☆495Oct 16, 2026Updated 2 weeks ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- R package EloML: Elo rating system for machine learning models☆28Jun 17, 2022Updated 4 years ago
- mlr3: Machine Learning in R - next generation☆1,084Oct 21, 2026Updated last week
- Fit interpretable models. Explain blackbox machine learning.☆6,971Updated this week
- Working with relational data models in R☆529Oct 10, 2026Updated 2 weeks ago
- Automation framework for machine learning, forecasting, model evaluation, and interpretation.☆252Sep 5, 2026Updated last month
- An R package for tidy stacked ensemble modeling☆303Oct 22, 2025Updated last year
- Time series analysis in the `tidyverse`☆645Aug 29, 2025Updated last year