Amazon Exam AIF-C01 Topic 5 Question 21 Discussion

Decision trees are an interpretable machine learning algorithm that clearly documents the decision-making process by showing how each input feature affects the output. This transparency is particularly useful when explaining how the model arrives at a certain decision, making it suitable for classifying genes into categories.

Option A (Correct): 'Decision trees': This is the correct answer because decision trees provide a clear and interpretable representation of how input features influence the model's output, making it ideal for understanding the inner mechanisms affecting predictions.

Option B: 'Linear regression' is incorrect because it is used for regression tasks, not classification.

Option C: 'Logistic regression' is incorrect as it does not provide the same level of interpretability in documenting decision-making processes.

Option D: 'Neural networks' is incorrect because they are often considered 'black boxes' and do not easily explain how they arrive at their outputs.

AWS AI Practitioner Reference:

Interpretable Machine Learning Models on AWS: AWS supports using interpretable models, such as decision trees, for tasks that require clear documentation of how input data affects output decisions.