Society of Actuaries (SOA) PA Practice Exam

What characterizes a leaf node in a decision tree?

1. It is the starting point of the tree

2. It has no child nodes

3. It represents a split in the data

4. It connects to the root node

The correct answer is: It has no child nodes

A leaf node in a decision tree is characterized primarily by its lack of child nodes. This means that once a decision has led to a leaf node, there are no further decisions or splits made; it signifies the end of the decision path. Leaf nodes serve as the final output of the decision-making process, often representing a classification or a final value in regression tasks. The fact that a leaf node does not have child nodes underscores its role in concluding a sequence of decisions based on the attributes of the dataset being analyzed. Therefore, the characteristics of leaf nodes are significant in understanding how the decision tree processes information and arrives at conclusions. In contrast, a starting point of the tree is known as the root node, which is the first decision point rather than a terminal one. Similarly, splits in the data occur at internal nodes rather than at leaf nodes. Leaf nodes do not connect back to the root but rather present the final decisions based on the preceding splits in the tree. This understanding of the structure and function of leaf nodes is crucial in interpreting decision trees in machine learning and data analysis.