@carstenhaubold I have tried a few things with the new Python integration and standard models and graphics seem to work quite well.
- h2o # there is obviously a knime implementation but for some advanced things it might be nice to have it
- xgboost
- lightgbm
- auto-sklearn
- autoxgb
- pycaret # no deep experience
- featuretools # feature generator
- miceforest # Missing value replacement
- prophet # time series analysis
- openpyxl # Excel Reader
- arrow
- orc
Question would be which ones should feature in a standard Python environment since experience unsers could always use a custom environment. Also I understood that there will be some development where you could build nodes based on Python - this might be a way to integrate specific packages (or would they use a central python environment?). Looking forward to this.
Another idea could be to also fully integrate a R version (though the variety of packages might be even larger). The Conda Environment propagation allows for the (well) propagation of a R version via conda/Miniconda - for Windows there are the R Windows Binaries - but maybe this could be a way for other operating systems too.