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Answer:
a. Clustering
Explanation:
The Expectation-Maximization (EM) algorithm is primarily used for clustering, especially in scenarios where the data contains hidden or latent variables. It is often used to find maximum likelihood estimates of parameters in probabilistic models, such as Gaussian Mixture Models (GMMs).