Question 6
Domain 1 — AI Concepts, Terminology, and Use CasesWhich of the following is an example of a generative model in machine learning?
Correct answer: D
Explanation
A Generative Adversarial Network is a generative model because it learns the underlying data distribution and can create new samples that resemble the training data. By definition, “generative” models produce data, unlike discriminative models that only classify or predict labels.
Why each option is right or wrong
A. Logistic Regression
B. Decision Tree
C. Support Vector Machine
D. Generative Adversarial Network (GAN)
A Generative Adversarial Network fits the definition of a generative model because it is trained to model the data distribution and synthesize new, realistic samples rather than merely assign labels. In the standard GAN framework, the generator learns from random noise to produce outputs that the discriminator cannot distinguish from real training data, which is the hallmark of generation rather than classification.
E. Naive Bayes Classifier
F. K-means Clustering