Difficulty: Easy
Correct Answer: All statements A–C are correct for standard practice
Explanation:
Introduction / Context:
Decision trees are graphical models used in analytics, machine learning, and decision analysis. This question checks whether you recognize the standard structural elements and the common left-to-right convention used to read many decision trees.
Given Data / Assumptions:
Concept / Approach:
A correct description should include node semantics and directional reading. Internal nodes represent conditional tests; branches correspond to test outcomes; leaves represent decisions or predicted classes. Many textbooks and tools draw the root at the left, though vertical or top-down layouts also exist. The essence, however, remains consistent across orientations.
Step-by-Step Solution:
1) Identify node roles: internal nodes are conditions; leaves are outcomes.2) Understand branching: each edge represents a possible result of the node’s test (e.g., yes/no, threshold comparisons).3) Recognize reading convention: commonly, the root is placed at the left and branches flow to the right (alternatively, top to bottom).4) Therefore, statements A, B, and C collectively describe standard practice.
Verification / Alternative check:
Whether the tree is drawn left-to-right or top-down, the semantics of nodes and branches do not change. Most references align with A–C as accurate descriptions.
Why Other Options Are Wrong:
Options that exclude any of A–C omit a standard aspect of decision trees and are thus incomplete.
Common Pitfalls:
Assuming orientation changes semantics. Orientation is a stylistic choice; node and branch meanings remain the same.
Final Answer:
All statements A–C are correct for standard practice.
Discussion & Comments