DALEX
DALEX copied to clipboard
moDel Agnostic Language for Exploration and eXplanation
Would be nice to have such a vignette and be able to convert it into a blog in the future.
The model factory part shall take care about archivisation of all required data and parameters Once model is created we shall have explainer and an entry in database
It should probably explain what's happening e.g. "specify variables to remove the warning" or "variable_splits overrides variables" https://github.com/ModelOriented/DALEX/blob/142c94d0aab51584a81e31c38d687a897b11cb60/python/dalex/dalex/predict_explanations/_ceteris_paribus/checks.py#L14-L16
Hi, I'm wondering if it would be possible (or even make sense) to have the option to specify random effects in the model explainer? I thought about this because when...
- code: https://github.com/NorskRegnesentral/shapr - paper: https://doi.org/10.1016/j.artint.2021.103502 - merge from https://github.com/jakubpw/DALEX
Wondering if DALEX will play nicely with sparklyr or if we can get this kind of information out of models & data in spark?
Closes #49
Hi, Following the example on https://pbiecek.github.io/DALEX/reference/plot.model_performance_explainer.html , if you rearrange the order of arguments from plot(mp_rf, mp_glm, mp_lm, geom = "boxplot", show_outliers = 1) to plot(mp_glm, mp_lm, mp_rf, geom =...
Hello, I am trying predict_parts_shap_aggregated () to predict the important variable features of a random forest model. However, I am getting this error - **Error in `.rowNamesDF