Our textbook describes in its Section 8.2.1 a basic algorithm for inducing a decision tree from training

tuples. The algorithm follows a top down approach, similar to how decision trees are constructed by

algorithms such as ID3, C4.5 and CART.

The execution of algorithm given in Section 8.2.1 is illustrated in Section 8.2.2, in Figure 8.5. The

illustration only shows the first two levels of the tree. Complete the example to show the entire

resulting decision tree. Include all nodes, branches and partitions.

age? middle agedsenior incomestudentcredit yating class high high medium no incomestudentcredityating class fair medium no no no no yes yes mediumyes medium no medium yes excellent income student credit-rating class high medium no no fair yes high fair Figure 8.5 The attribute age has the highest information gain and therefore becomes the splitting attribute at the root node of the decision tree. Branches are grown for each outcome of age. The tuples are shown partitioned accordingly