What is a Gaussian Mixture Model (GMM)?
A Gaussian Mixture Model describes an underlying distribution that is composed of multiple individual Gaussian distributions
A Gaussian Mixture Model describes an underlying distribution that is composed of multiple individual Gaussian distributions
Expectation-Maximization refers to a two-step, iterative process that is often used when latent or unobserved variables are present underlying a data generation process.
When used for clustering, any of the evaluation metrics (Silhouette Score, Dunn Index, Rand Index, etc.) are appropriate
K-Means aims to minimize the Within Cluster Sum of Squares, while EM aims to maximize the likelihood of an underlying probability distribution.
Pros: Has the ability to find more local clusters that K-Means would not be able to differentiate
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