I would like to use machine learning to determine the race of an individual based on things like the first letter of his/her name, my problem is that the data I have is distributed in the following way:
COUNT RACE 92742 African 12 Asian 43349 Mixed race 327 Foreign National 4588 Indian 11179 White
So the data is very skewed in terms of volume towards African and Mixed race. When training my learner will this affect the learning and what should I do to combat this? Also instead of the first letter of the name (A-Z) should I use the number representation of the alphabet letter (1-26) or even a representative value between 0 and 1?