EMCluster

R package EMCluster: EM Algorithm for Model-Based Clustering of Finite Mixture Gaussian Distribution. EM algorithms and several efficient initialization methods for model-based clustering of finite mixture Gaussian distribution with unstructured dispersion in both of unsupervised and semi-supervised learning

Keywords for this software

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References in zbMATH (referenced in 6 articles )

Showing results 1 to 6 of 6.
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  1. Michael C. Thrun, Quirin Stier: Fundamental clustering algorithms suite (2021) not zbMATH
  2. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
  3. Alexander Foss; Marianthi Markatou: kamila: Clustering Mixed-Type Data in R and Hadoop (2018) not zbMATH
  4. Fop, Michael; Murphy, Thomas Brendan: Variable selection methods for model-based clustering (2018)
  5. Michael, Semhar; Melnykov, Volodymyr: An effective strategy for initializing the EM algorithm in finite mixture models (2016)
  6. Marcos Prates; Victor Lachos; Celso Barbosa Cabral: mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions (2013) not zbMATH