Hi, I am going to use RF classification on S-1 images, and I would like to confirm a few things about on how RF works on SNAP. From the posts I have read,
- the Evaluate classifier is about training accuracy and not accuracy assessment of the classified image,
- So, accuracy assessment has to be done in another software,
- The number of the training samples is the number of the pixels that will be used from each vector I have imported (when train on vector is selected) for the training of the algorithm,
- RF splits training data to 2/3 for training and 1/3 for an internal cross-validation.
In the number of the training samples, the number that I am typing is the 2/3 or the 3/3 of the available pixels of each trained class?