Random Forest NAN at Confidence values below 0.5

@dreckbolle: This solution is not SNAP related, but I achieved great results with the ENMaP-Toolbox.
You need the IDL virtual machine (installation of IDL, needs no license) for it and can load the DIMAP rasters directly into the program.
You can also import Shapefiles as training vectors so no conversion of your data is needed.

Also its computing time is impressive (raster with 5000*8000 and 50 bands takes about 3 minutes). Is quite simple to use and allows for changes in the RF parametrization.

  1. import the rasters
  2. stack the rasters
  3. import the vectors as classified raster
  4. train the RF model
  5. apply the RF model