I am back to this classification issue because I could not find a way to have it working the way I need. Let's keep it simple: my need is to do a SML with only one class. As far as I know, in other softwares (e.g. ENVI) it is possible to make it with only one class, and then specify a likelihood threshold (as a precentage), to which each pixel in the image to be classified is assigned or not to the class. In GRASS I think it would work similarly, in the sense that I don't specify any percentage of likelihood, but I can look at the reject map. Still, I don't understand why over the ROIs I have more rejection than elsewhere. Shouldn't it be the opposite? I know I already asked so, but it's important for me to understand if something I am doing is wrong. Thanks for any hints or help, it would be very much appreciated.
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