You may configure these error messages like configuring other properties of validators in a validation rule.
The method will return a boolean value indicating whether the validation succeeded or not.Things to look for: have past clients been able to implement the results from their model? Hopefully, overall revenue increased after implementing these results (and did not only increase for some channels, and decrease for others due to a shift in media budget).In order for an attribution model to be effective, it has to shift spend in a way that increases the ROI overall.Model validation that is based on statistical inference seeks to construct a statistical comparison of model predictions against measurements of the target process.
Previously, such validation has commonly used the hypothesis of no difference as the null hypothesis, that is, the null hypothesis is that the model is acceptable.
That said, I still believe that for an attribution model to be trustworthy and for marketers to be able to pull out actionable insights from it, it is imperative that we provide some measure of model validity.