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chrisfs (2) [Avatar] Offline
This may be a tangent.
On page 11, the text reads :"The input data in turn consist of a set of features–numerical or categorical metrics that
capture the relevant aspects of each application–such as the credit score of the applicant,
their gender, and their current occupation.".
It is very likely that taking gender into account for loan approval is illegal. While this doesn't matter to the point of machine learning, it would be a good deal to use legal examples throughout the book.
henrik.brink (22) [Avatar] Offline
Re: Gender in loan approval?
Hi there, thank you for your comments!

I personally don't think it makes sense to remove this because it might be illegal in some parts of the world. This is about the machine learning modeling and you should use whatever data you can to get the results you want. If you are constrained legally or financially, then it's up to you to make the decision about which features to use.