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Expectation-Maximization (EM) Algorithm
A computational method used to find maximum likelihood estimates of parameters in models with latent variables.
Implications
A statistical method used to find maximum likelihood estimates of parameters in models with latent variables, often used in machine learning, data clustering, and incomplete data scenarios.
Example
Example: An analyst uses the EM algorithm to estimate the parameters of a Gaussian mixture model, identifying distinct customer segments based on purchase behavior.
Related Terms
Different from simple optimization methods, the EM algorithm alternates between estimating latent variables and optimizing parameters, handling cases where direct optimization is challenging.
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