Please explain as best you can how to get the answer(with theory) and I will give you a thumbs up. Don't simply use chat GPT.

(d) Denote the probability density functions (PDFs) of some random samples in K classes as {p(xCk)}k=1K, where x represents a random sample and Ck denotes the k-th class. Assume that the classes have equal prior probabilities, i.e., P(Ck)=P(Cj)k=j. (i) Explain how you would construct a classifier based on the posterior probabilities of individual classes. You may need to use equations to explain your answer. (5 marks) (ii) If the prior probability of the k-th class is significantly smaller than that of the others, i.e., P(Ck)P(Cj)j=k, discuss the condition on p(xCk) for which the classifier will consider xi as belonging to Class k. (4 marks)