AWS Certified Machine Learning – Specialty — Question 93

A Machine Learning Specialist is deciding between building a naive Bayesian model or a full Bayesian network for a classification problem. The Specialist computes the Pearson correlation coefficients between each feature and finds that their absolute values range between 0.1 to 0.95.
Which model describes the underlying data in this situation?

Answer options

• A. A naive Bayesian model, since the features are all conditionally independent.
• B. A full Bayesian network, since the features are all conditionally independent.
• C. A naive Bayesian model, since some of the features are statistically dependent.
• D. A full Bayesian network, since some of the features are statistically dependent.

Correct answer: D

Explanation

The correct answer is D because a full Bayesian network is suited for situations where some features exhibit statistical dependence, as indicated by the varying Pearson correlation coefficients. Options A and B incorrectly assume conditional independence among features, while option C mistakenly suggests that a naive Bayesian model is appropriate despite the presence of dependence.