Additive biclustering: a comparison of one new and two existing ALS algorithms

DOI10.1007/s00357-013-9120-0zbMath1360.62364OpenAlexW2032608475MaRDI QIDQ288849

Iven van Mechelen, Dirk Depril, Tom Frans Wilderjans

Publication date: 27 May 2016

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

Full work available at URL: https://doi.org/10.1007/s00357-013-9120-0

zbMATH Keywords

simulation studytwo-mode clusteringadditive clusteringALS algorithmsbiclusteringco-clusteringPENCLUSsimultaneous overlapping clusteringstwo-mode data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Clustering in the social and behavioral sciences (91C20)

Related Items (4)

Kernel-based methods to identify overlapping clusters with linear and nonlinear boundaries ⋮ Deriving optimal data-analytic regimes from benchmarking studies ⋮ Model selection strategies for determining the optimal number of overlapping clusters in additive overlapping partitional clustering ⋮ An exact algorithm for the two-mode \(KL\)-means partitioning problem

Uses Software

• ADPROCLUS

Cites Work

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• Improved biclustering of microarray data demonstrated through systematic performance tests
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• The CHIC model: a global model for coupled binary data
• GENNCLUS: New models for general nonhierarchical clustering analysis
• An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models
• An error variance approach to two-mode hierarchical clustering
• Additive two-mode clustering: The error-variance approach revisited
• Initializing \(K\)-means batch clustering: A critical evaluation of several techniques
• Two-mode clustering methods: astructuredoverview

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