Q6 — AWS AIF-C01 Ch.2

Question 6 of 100 | ← Chapter 2

A company wants to classify human genes into 20 categories based on genetic features. The company requires a machine learning method that can explain how the model's internal mechanisms influence its output. Which machine learning method satisfies these requirements?

• A. Decision tree ✓
• B. Linear regression
• C. Logistic regression
• D. Neural network

Correct Answer: A. Decision tree

Explanation

The decision tree algorithm satisfies the company's requirement to classify human genes based on genetic features while explaining how the model's internal mechanisms influence its output. Decision trees recursively split the dataset based on feature values, forming a tree-like structure that intuitively shows how decisions are made at each node. This structure clearly illustrates the model's internal decision-making process. In contrast, linear regression is used for predicting continuous values, and logistic regression is designed for binary classification—neither provides intuitive insight into internal decision logic. Neural networks, although powerful, have complex internal mechanisms that are difficult to interpret at the level of individual neurons and weights. Therefore, the decision tree is the most suitable machine learning algorithm for this requirement.