DALEX is an R package for visual explanation, exploration, diagnostic and debugging of predictive ML models (aka XAI – eXplainable Artificial Intelligence). It has a bunch of visual explainers for different aspects of predictive models. Some of them are useful during model development some for fine tuning, model diagnostic or model explanations.
Recently Hanna Dyrcz designed a new beautiful theme for these explainers. It’s implemented in the `DALEX::theme_drwhy()` function.
Find some teaser plots below. A nice Interpretable Machine Learning story for the Titanic data is presented here.
Hanna is a very talented designer. So I’m super happy that at the next satRdays @ gdansk2019 we will have a joint talk ,,Machine Learning meets Design. Design meets Machine Learning”.
New plots are available in the GitHub version of DALEX 0.2.8 (please star if you like it/use it. This helps to attract new developers). Will get to the CRAN soon (I hope).
Instance level explainers, like Break Down or SHAP
Instance level profiles, like Ceteris Paribus or Partial Dependency
Global explainers, like Variable Importance Plots
See you at satRdays!