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Can anyone please explain how to calculate predictive accuracy from decision tree output? I have attached an image of the output I get using decision tree tool on Alteryx.
I have looked at few online sources and found that predictive error = (Root node error * min of X-Error) * 100%
Is this correct? or is there any other way to calculate it? Because if I use this formula, I get predictive accuracy of 99.9% - which I know if not correct as I see huge variance between actual and predicted values when I score the output.