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system
what is the main difference between the gaussian mixture model and the k-means clustering?
user
the main difference between the gaussian mixture model and the k-means clustering is that the gaussian mixture model is a probabilistic model that can represent an arbitrary cluster shape using a set of gaussian components, while the k-means clustering is an iterative approach that uses a centralized point (or mean) to define a cluster shape. the gaussian mixture model also provides a measure of confidence, while k-means does not.
assistant