n 2022 Jeff, a data analyst at JDC research center, was tasked to build a model that can be used as a preliminary diagnostic tool for the disease uberculosis. In this new tool, a patient would be asked a series of questions about themselves. The answers provided will be treated as redictor attributes of the patient from which a trained model can then predict whether or not the patient has tuberculosis. To build his model, eff used historical data of 1,000 patients who were screened for tuberculosis between 1935 and 1940.0 the 1,000 patients, 2 of them had uberculosis. Jeff built his model using the whole dataset as training data and then re-evaluated his model on the same data. Jeff was very appy with his model because it worked extremely well on his training dataset with near perfect accuracy. Jeff wrote an online article about his nodel which received several criticisms. a. With your background in data mining, determine with justification the type of learning task Jeff must have performed with two labels from the following \{Clustering, supervised learning, unsupervised learning, regression, classification\}. [3 marks] b. Can you identify and explain any technical reasons Jeff may have received criticisms on his article? For each reason, suggest a remedy. [12 marks]