For regression trees, the most likely goodness-of-fit measure is
_(_())_(_())

_(_())_(_())
mean square-root error
◻
misclassification cost
◻
entropy
◻
sum of squared errors

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For regression trees, the most likely goodness-of-fit measure is _(_())_(_()) _(_())_(_()) mean square-root error  misclassification cost  entropy  sum of squared errors

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