In the real world, lots of changes may occured between the data used to train your model and the one used to make your prediction. Particularly if training and prediction are done within different timeframes. These changes are defined by the phenomenon of covariate drift. Which corresponds to a distribution difference of the explanatory variables of your model between training and prediction set.
The goal of this article is not to give you a detailed solution to overcome your model obsolescence but only how to detect it. It is in fact the first step.
Detecting a model obsolescence is directly…
Maybe your job interviewer asked you about lift curve and you nearly had a heart attack, or maybe you are curious about that curve with a catchy name you heard about? It could be a lot more of possibilities I guess, but don’t worry, I think you found the article you needed!
In this article, you won’t find any code nor complex math formulas. I will try to explain you how to build a lift curve and its application in a digital marketing use case and also how it can be used to evaluate a classification model.