Hello all, I’m studying with Satellite Image Classification, especially Random Forest.
There are some questions when I perform Random Forest Classifier in SNAP.
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I wonder Random Forest Classifier’s mechanism in SNAP. I searched but I couldn’t get clear answers.
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Default value of “Number of training samples” set 5000, what does it mean?
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When RF process is done, we can get confusion matrix written Text file named newClassifier.
‘Predictive Values’ depend on pixel feature in Training vectors I guess. Then what is the criteria of ‘Actual Values’ ? How can the classifier decide TP, TN, FP, FN and accuracy ?
Thanks for reading.