Michael Oliver said that if your feature exposure is too high, you'll have more variance, and if it's too low your model will have too low of a mean. He added that if you're interested in feature exposure, look at the distribution of your scores and find your maximum feature exposure. "Each feature exposure is a risk," Michael Oliver said, "and if you still have some very high risks, that might get covered up by other ones you're low on."