comparing Gaussian mixtures and k-means

Summary

Gaussian mixture models and K-means are two canonical approaches to clustering, i.e. dividing data points into meaningful groups. This concept node discusses the tradeoffs between them.

Context

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-Free-

Bayesian Reasoning and Machine Learning
A textbook for a graudate machine learning course.
Author: David Barber

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See also

  • Other clustering methods include: The application of clustering to finding meaningful regions of images is called image segmentation .