Comments (1)
Hi. This can be done by transforming variable before fitting the model.
Perhaps you want to predict a non-negative variable like the price or quantity. Let the variable be y
. Then you need to define new variable lny = ln(y)
, fit the model on lny
, make a prediction lny_pred
and apply inverse transformation exp(lny_pred)
. Or you can use sqrt
instead of ln
and x ** 2
instead of exp
.
But be careful because such transformations tend to bias the estimates of expectation and confidence intervals. If you need to get unbiased estimates, then you need to either calculate a correction for the resulting forecast or conduct a Monte Carlo.
References:
- Mathematical transformations
- Bias adjustments
- Identifying and Overcoming Transformation Bias in Forecasting Models
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