Model-Based Clustering with Measurement or Estimation Errors

Model-Based Clustering with Measurement or Estimation Errors

Model-based clustering with finite mixture models has become a widely used clustering method. One of the recent implementations is MCLUST. When objects to be clustered are summary statistics, such as regression coefficient estimates, they are naturally associated with estimation errors, whose covari...

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Bibliographic Details
Main Authors: Wanli Zhang, Yanming Di
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Genes
Subjects:
gaussian finite mixture model
clustering analysis
uncertainty
expectation-maximization algorithm
classification boundary
gene expression
rna-seq
Online Access:https://www.mdpi.com/2073-4425/11/2/185

Internet

https://www.mdpi.com/2073-4425/11/2/185

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