By using ethnicity as a sensitive field, and comparing disparity between selection rates and performance metrics for each ethnicity value, you can evaluate the fairness of the model.
Hmm, this is a tricky one. I was sure Aggregation was a common technique, but let me think this through. Oh, I got it! Aggregation is the answer that doesn't fit with the rest.
A) Scaling, B) Encoding, and D) Normalization are all types of Feature Engineering Transformation. I'm pretty sure C) Aggregation is the odd one out here.
Sabra
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