Question: Suppose we have created a model that considers a certain number of features and the model performance is acceptable. Later we learn new information that

Suppose we have created a model that considers a certain number of features and the model performance is acceptable. Later we learn new information that the value of the XYZ feature makes sense only if it is positive (i.e XYZ > 0 in the model instead of the original). How do we tackle this problem?

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