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I am trying to understand the basics of random forest machine learning applied to vegetation classification. Do I understand correctly that the output/leaf node of each individual decision tree contains a single class?

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Yes, the regularization which is typically done on decision trees which makes the leaves non-pure is not needed in random forests due to the structure of the algorithm.

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