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Expectation maximization ( EM ) is designed to find a maximum likelihood setting of the parameters of model when some of the data is missing.
Expectation maximization EM is designed to find a maximum likelihood setting
of the parameters of model when some of the data is missing. Does the algorithm
converge? If so do you obtain a locally or globally optimal set of parameters?
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