Mixture models are also known as Model-based-clustering.
Model-based clustering is a broad family of algorithms designed to model an unknown distribution as a mixture of simpler distributions, sometimes called base distributions.
The mixture model:
The mixture model is a probabilistic model for representing the presence of subpopulations within an overall population without requiring an observed data set to identify the subpopulation to which an individual observation belongs.
A mixture model is the mixture distribution that represents the probability distribution of observations in the overall population.
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