I dont know parameter whose status will be leaf part of decision tree it wasn't given to us. This is all that was given

Problem Statement: 1. Decision Tree(DT) Apply the DT algorithm to the training data provided in the following data. Please show all calculations justifying your answer a. Training FeverVomitingDiarrhea |Shivering |Classification dl d2 d3 d4 d5 d6 d7 healthy(H) influenza(T) influenza(T) Salmonella poisoning (S) Salmonella poisoning (S Bowel inflammation (B) Bowel inflammation (B) no no no no average no no no hi no no yes hi yes yes yes yes yes no average no no no yes no average [yes no b. Does the resulting decision tree provide a disjoint definition of the classes? Problem Statement: 1. Decision Tree(DT) Apply the DT algorithm to the training data provided in the following data. Please show all calculations justifying your answer a. Training FeverVomitingDiarrhea |Shivering |Classification dl d2 d3 d4 d5 d6 d7 healthy(H) influenza(T) influenza(T) Salmonella poisoning (S) Salmonella poisoning (S Bowel inflammation (B) Bowel inflammation (B) no no no no average no no no hi no no yes hi yes yes yes yes yes no average no no no yes no average [yes no b. Does the resulting decision tree provide a disjoint definition of the classes