Hello forum@sentinel hub,
I have been trying to make a custom version of the example in land-cover-classification-with-eo-learn tutorials.
Unfortunately I find that the result of my classification is that PointSamplingTask only finds 3 feature classes, out of 10 in total. As I understood in the example it takes 40.000 pixels from 1.000.000 pixels. I have tried with the PointSamplingTask set to 800.000 pixels as an experiment, and it did find more feature classes but it caused the GBM machine learning algorithm to overfit.
Therefore my question: is there a way to set a minimum amount (for example 20.000 pixels) for every unique feature class for the PointSamplingTask?
Thanks a lot in advance,
Thijs
