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Description of Problem:
Data drift is not necessarily sufficient to explain evolution of performance of deployed model.
The concept drift would complete the explanation of the evolution of performance. And in addition, to project the future behaviour of the model
Overview of the Solution:
A first solution is to re-train the same type of model on df_baseline and df_current. And then compare the explainability of these two models. This comparison can be done with the Shapash library
The text was updated successfully, but these errors were encountered:
Description of Problem:
Data drift is not necessarily sufficient to explain evolution of performance of deployed model.
The concept drift would complete the explanation of the evolution of performance. And in addition, to project the future behaviour of the model
Overview of the Solution:
A first solution is to re-train the same type of model on df_baseline and df_current. And then compare the explainability of these two models. This comparison can be done with the Shapash library
The text was updated successfully, but these errors were encountered: