EM algorithm applications

The Expectation-Maximization (EM) algorithm is a statistical technique used to find hidden patterns in data, especially when some information is missing or incomplete. It is commonly applied in fields like machine learning, image processing, and bioinformatics. For example, in clustering similar data points or refining models for tasks like speech recognition and genetic analysis, EM helps improve accuracy. By iteratively estimating missing data and optimizing parameters, this algorithm enhances our understanding of complex datasets and enables better decision-making based on incomplete information.