EM-based Clustering Algorithm

An EM-based Clustering Algorithm is a clustering algorithm that … Expectation Maximization Algorithm.

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• Example(s):
  • …
• Counter-Example(s):
  • Distance-based Clustering.
• See: Ordered-Subset EM Algorithm, Mixture Model Clustering.

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References

2012

• http://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm#Applications
  • EM is frequently used for data clustering in machine learning and computer vision. In natural language processing, two prominent instances of the algorithm are the Baum-Welch algorithm (also known as forward-backward) and the inside-outside algorithm for unsupervised induction of probabilistic context-free grammars.

2011

• (Jin & Han, 2011b) ⇒ Xin Jin; Jiawei Han. (2011). “Expectation Maximization Clustering.” In: (Sammut & Webb, 2011) p.382

1999

• (Moore, 1999) ⇒ Andrew W. Moore. (1999). “Very Fast EM-based Mixture Model Clustering Using Multiresolution Kd-trees." Advances in Neural information processing systems
• (Rooth et al., 1999) ⇒ Mats Rooth, Stefan Riezler, Detlef Prescher, Glenn Carroll, and Franz Beil. (1999). “Inducing a Semantically Annotated Lexicon via EM-based Clustering.” In: Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics on Computational Linguistics, pp. 104-111 . Association for Computational Linguistics,

1998

• (Moore, 1998) ⇒ Andrew Moore. (1998). “Very Fast EM-Based Mixture Model Clustering Using Multiresolution kd-Trees.” In: ProceedingsConf. Neural Information Processing Systems (NIPS 1998).

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