How can you combine K$-$means clustering and Bayesian to select the most suitable restaurant for the given user? The available data is $\{$age$,$ taste, choice of food and details of friends$\}$ and $\{$restaurant location, food menu, ambience and ratings$\}.$ Provide algorithm for learning and also

for testing. Discuss a technique where supervised learning is followed by unsupervised learning for decision

making. How can it be used in case of recruitment? Here recruitment agent gets bio$-$data and

interview discussions of interviewers with candidates as inputs. Write an algorithm to support

your description.