hard20 pts · first answer countsregressionforecasting

Back-transforming log predictions

You fit a model to log(revenue) and report exp(prediction) as expected revenue per customer. Summed over customers, the forecast comes in well below actual revenue. Why?

A.The log transform made the model overfitB.exp() cannot be applied to negative predictionsC.exp of the mean of log(y) estimates the median, not the mean, so it underestimates on skewed dataD.Revenue must be standardised before taking logs

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Back-transforming log predictions

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