In machine learning, which type of model learns the entire data distribution to create new examples that resemble the training data?
Reinforcement learning model
Discriminative model
Generative model
Clustering model
Generative models learn the entire data distribution, allowing them to create new data instances similar to those in the training set.
Discriminative models focus on modeling the decision boundary between classes for tasks like classification but do not generate new data.
Reinforcement learning models learn optimal actions based on rewards but are not designed to model data distributions or generate new examples.
Clustering models group similar data points but do not create new data instances.
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