- The number of trees defines how often the training data (under different conditions, some data left out) is trained against the pixel values. For testing, 10 is enough but to achieve robust results, you can increase it up to 100 or 500. This however only makes sense if you have more than 8 input rasters, otherwise the training data is always the same, even if you repeat it 1000 times.
- The number of samples is the number of pixels within your training polygons which are randomly selected for training. This means, each trained class should have clearly more than 5000 pixels, otherwise you always use the same available pixels.
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