Studying Complexity of Model-based Clustering
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Publication:2816737
DOI10.1080/03610918.2014.889156zbMath1347.62116OpenAlexW2157451982MaRDI QIDQ2816737
Volodymyr Melnykov, Semhar Michael
Publication date: 25 August 2016
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2014.889156
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05)
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Uses Software
Cites Work
- Generation of random clusters with specified degree of separation
- OCLUS: an analytic method for generating clusters with known overlap
- Initializing the EM algorithm in Gaussian mixture models with an unknown number of components
- Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
- Separation index and partial membership for clustering
- A mixture of experts model for rank data with applications in election studies
- Estimating the dimension of a model
- Model-based clustering of high-dimensional data: a review
- Comparing clusterings -- an information based distance
- Finding Groups in Data
- How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
- Model-Based Clustering, Discriminant Analysis, and Density Estimation
- Variable Selection for Model-Based Clustering
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