Hello,

I am having some difficulty arriving at the correct solution to this problem

Overall I am not confident in my approach when solving this problem and I would like to kindly compare and learn how to properly solve this problem.

In specifics, when I get .31 for the positive label and .69 for the negative label probability I'm not sure if it just claims that the Bayes classifier results in a negative classification. also, I'm confused in solving for the expected square loss. , I might be overlooking an error or might be overcomplicating for myself.

In-depth Steps with explanations are greatly appreciated, as it would help me with learning the whole process and finding my error!

Thank you very much for your expert help!

Problem 1. The feature space consists of three possible points (events) 141,330} which occur with probability 0.10.3305, respectively. For each event there are two possible labels +1 or 1, which occur with probability 0.7,04 and 0.1 respectively (that is, P(1|A) : 0.7,P(1|B) : O.4,P(1|C) : 0.1). Determine the Bayes optimal classier (as a function of the event, A,B,C). What is the expected (classication) loss of the Bayes optimal clas- sier? Find the regression function and compute its expected (square) loss