Additive clustering and qualitative factor analysis methods for similarity matrices

DOI10.1007/BF01890073zbMath0617.62064MaRDI QIDQ1822172

Boris G. Mirkin

Publication date: 1987

Published in: Journal of Classification (Search for Journal in Brave)

zbMATH Keywords

algorithmsconvergence propertiesadditive clusteringsimilarity matrixqualitative factor analysis

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (13)

Kernel-based methods to identify overlapping clusters with linear and nonlinear boundaries ⋮ An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models ⋮ Cluster analysis and mathematical programming ⋮ Additive two-mode clustering: The error-variance approach revisited ⋮ Sequential clustering with radius and split criteria ⋮ ROOTCLUS: searching for ``ROOT clusters in three-way proximity data ⋮ Community detection in feature-rich networks using data recovery approach ⋮ Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach ⋮ Improved biclustering of microarray data demonstrated through systematic performance tests ⋮ Identifying Multiple Cluster Structures in a Data Matrix ⋮ Summary and Semi-average Similarity Criteria for Individual Clusters ⋮ On the complexity of additive clustering models ⋮ A sequential fitting procedure for linear data analysis models

Uses Software

• MAPCLUS
• Indclus

Cites Work

• MAPCLUS: A mathematical programming approach to fitting the ADCLUS model
• Constructing blockmodels: how and why
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