Záznam dôkazov metódy

Gaussian Mixture Model

A Gaussian Mixture Model is a probabilistic clustering method that models the data as a weighted mixture of several Gaussian distributions, fitted with the Expectation–Maximization algorithm formalized by Dempster, Laird & Rubin in 1977. It is a generalization of K-means in which each cluster can take its own shape, size, and orientation.

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Gaussian Mixture Model (GMM Clustering)

Taxonomický záznam metódy · ml-model / machine-learning

Dempster, A.P., Laird, N.M. & Rubin, D.B. (1977). Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society: Series B, 39(1), 1–22. · DOI 10.1111/j.2517-6161.1977.tb01600.x

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Same method familyDBSCANmachine-suggested · Relational suggestion, not evidence.Same method familyHierarchical Clusteringmachine-suggested · Relational suggestion, not evidence.Same method familyPrincipal Component Analysismachine-suggested · Relational suggestion, not evidence.Same method familyUMAPmachine-suggested · Relational suggestion, not evidence.