All four are forms of supervised learning methods. All four use labeled data models. You are using Naive Bayes classification to predict if the patient has flu. According to the historical data, we have the following knowledge:
chills runny nose headache fever flu? Y N Mild Y N Y Y No N Y Y N Strong Y Y N Y Mild Y Y N N No N N N Y Strong Y Y N Y Strong N N Y Y Mild Y Y
Now there is a new patient who has chills, runny nose, but no headache or fever. Is the patient predicted to have a flu? Please show the calculation. Following the previous example, please draw a decision tree to classify if someone has the flu. Note: you don't have to optimize the decision tree by calculating the entropy. Any decision tree is acceptable if it is correct for the above table.