Assignment task: For almost every case we have discussed where we are doing Supervised learning, we have assumed a deterministic function. Irnagine instead a world where we are trying to capture a non-deterministic function. In this case. We might see training pairs where the 3: value appears several times, but with different 3* values. For example, we might be mapping attributes of humans to whether they are likely to have had chicken pox. In that case, we might see the same kind of person many times but sometimes they will have had chicken pox, sometimes not. "re would like to build a learning algorithm that will compute the probability that a particular kind of person has chicken pox. So, given a set of training data where each X is mapped to 1 for true or i] for false:
1. Derive the proper error function to use for finding the ML hypothesis using Bayes Rule. You should go through a similar process as the one used to derive least squared error in the lessons.