9 Suppose a patient can have multiple severity of a disease (D) = {mild, moderate, severe that may cause three different

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9 Suppose A Patient Can Have Multiple Severity Of A Disease D Mild Moderate Severe That May Cause Three Different 1 (73.11 KiB) Viewed 104 times

9 Suppose a patient can have multiple severity of a disease (D) = {mild, moderate, severe that may cause three different symptoms to show, Fever (A), Cough (B) and Shortness of Breath (C). The different severity of the disease may cause multiple symptoms to show at the same time, but sometimes symptoms may not show at all. (a) Construct a Naive Bayes' machine learning model by drawing the arrows in Fig. 29: A B D Fig. 29 (b) Suppose we have the data of 16 patients with different levels of severity and manifestation of symptoms (T means the symptom exist; F means the symptom does not exist): A B F F С F F D Mild Mild Mild Mild Mild Moderate Moderate Moderate T F F F F T T F B T T F 1 F T F D Moderate Moderate Moderate Severe Severe Severe Severe Severe F F T F 1 T А F T T T F F 1 T C F F F F F T T F F T T F F F 1 What is the maximum likelihood estimate of the prior P(D)? P(D) Mild Moderate Severe
(c) What is the maximum likelihood estimates of the conditional probability distributions? Fill in the tables below. PAD P(BD) P(CD) Mild T Mild T Mild T Mild F. Mild F Mild F Moderate T Moderate T Moderate T Moderate F Moderate F Moderate F Severe T Severe T Severe T Severe F Severe F Severe F (d) Suppose we now have a new data point (A, B, C) = (T, F, T). Use your classifier to determine the joint probability of the disease D and this new data point, as well as the posterior probability of the disease D given the new data point, P(D, A = T, B = F, C = T) Mild P( DA = T, B = F, C = T) Mild Moderate Moderate Severe Severe (e) Which severity level does your classifier give to the new data point?