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A company deployed an AI/ML solution to help customer service agents respond to frequently asked questions. The questions can change over time. The company wants to give customer service agents the ability to ask questions and receive automatically generated answers to common customer questions. Which strategy will meet these requirements MOST cost-effectively?
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.