Most optimization problems can trivially be turned >into a statistics problem.
Sure if you mean turning your error function into some sort of likelihood by employing probability distributions that relate to your error function.
But that is only the beginning. Apart from maybe Bayesian neural networks, I haven’t seen much if any work on stuff like confidence intervals for your weights or prediction intervals for the response (that being said I am only a casual follower on this topic).
Sure if you mean turning your error function into some sort of likelihood by employing probability distributions that relate to your error function.
But that is only the beginning. Apart from maybe Bayesian neural networks, I haven’t seen much if any work on stuff like confidence intervals for your weights or prediction intervals for the response (that being said I am only a casual follower on this topic).