Automatic Selection of Number of Clusters in Networks Using Relative Eigenvalue Quality

2013 ◽  
Author(s):  
John M. Shea ◽  
Joseph P. Macker
Keyword(s):  
Number Of Clusters ◽  
Automatic Selection ◽  
Selection Of

Automatic selection of the number of clusters using Bayesian clustering and sparsity‐inducing priors

2021 ◽  
Author(s):  
Denis Valle ◽  
Yusuf Jameel ◽  
Brenda Betancourt ◽  
Ermias T. Azeria ◽  
Nina Attias ◽  
...  
Keyword(s):  
Bayesian Clustering ◽  
Number Of Clusters ◽  
Automatic Selection ◽  
Selection Of

Cluster Analysis of Antigenic Profiles of Tumors: Selection of Number of Clusters Using Akaike’s Information Criterion

1990 ◽  
Vol 29 (03) ◽  
pp. 200-204 ◽  
Author(s):  
J. A. Koziol
Keyword(s):  
Cluster Analysis ◽  
Basic Problem ◽  
Information Criterion ◽  
Akaike's Information Criterion ◽  
Cell Surface Antigens ◽  
Number Of Clusters ◽  
Akaike’S Information Criterion ◽  
Multinomial Data ◽  
Tumor Types ◽  
Selection Of

AbstractA basic problem of cluster analysis is the determination or selection of the number of clusters evinced in any set of data. We address this issue with multinomial data using Akaike’s information criterion and demonstrate its utility in identifying an appropriate number of clusters of tumor types with similar profiles of cell surface antigens.

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