Expectation Maximization Clustering

The expectation maximization (EM) based clustering is a probabilistic method to partition data into clusters represented by model parameters. Extensions to the basic EM algorithm include but not limited to the stochastic EM algorithm (SEM), the simulated annealing EM algorithm (SAEM), and the Monte...

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Bibliographic Details
Published inEncyclopedia of Machine Learning and Data Mining pp. 480 - 482
Main Authors Jin, Xin, Han, Jiawei
Format Book Chapter
LanguageEnglish
Published Boston, MA Springer US 2017
Online AccessGet full text
ISBN9781489976857
148997685X
DOI10.1007/978-1-4899-7687-1_344

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Summary:The expectation maximization (EM) based clustering is a probabilistic method to partition data into clusters represented by model parameters. Extensions to the basic EM algorithm include but not limited to the stochastic EM algorithm (SEM), the simulated annealing EM algorithm (SAEM), and the Monte Carlo EM algorithm (MCEM).
ISBN:9781489976857
148997685X
DOI:10.1007/978-1-4899-7687-1_344