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?
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.

Question

Quizplus · Accepted Answer

A naive Bayesian model assumes conditional independence between features, which is not the case here as the Pearson correlation coefficients indicate statistical dependence between some features. Therefore, a full Bayesian network is more appropriate in this situation.

A Machine Learning Specialist Is Deciding Between Building a Naive