Automatic documentation seems to be an advatage. But what about explainabity?
There is explanation of ML models and predictions:
- learning curves from training
- decision tree visualization
- linear model coeffs printout
- features importance (permutation based)
- SHAP features importance
- SHAP dependence plots
- SHAP decision plots