How so? It is a supervised learning problem: you have DNA markers as input features and self-reported race as the target class. If the model reaches >99% accuracy (*) I would say it performs pretty well.
The point I wanted to make is that in the real world models in this area don’t have >99% accuracy.
Would this South American “native” self-identify as “black”?
That depends on the social environment. If they want to apply to an university that has a quota for Black students it wants to accept and their skin color is Black, there a good chance that they will put Black in the field that asks for the race.
The point I wanted to make is that in the real world models in this area don’t have >99% accuracy.
That depends on the social environment. If they want to apply to an university that has a quota for Black students it wants to accept and their skin color is Black, there a good chance that they will put Black in the field that asks for the race.
The link many comments up suggests that we do in fact have >99% accuracy (when limited to major ethnic groups in the US).