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  • Search: subject:"Overlapping clustering"
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Subject
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Overlapping clustering 4 overlapping clustering 4 ADCLUS 3 Cluster analysis 2 cluster analysis 2 Additive clustering 1 Additive overlapping clustering 1 Additive tree 1 Alternating least squares algorithm 1 Clique 1 Clusteranalyse 1 Competition 1 Consumer behaviour 1 Dimensional reduction 1 Dissimilarities 1 Extended tree 1 Graph 1 Hierarchical Classes Analysis 1 INDCLUS 1 Konsumentenverhalten 1 MAPCLUS 1 Market structure 1 Marktstruktur 1 Neural networks 1 Neuronale Netze 1 Object by variable data 1 Parsimony 1 Phylogenetic trees 1 Proximities 1 Regional cluster 1 Regionales Cluster 1 Separability 1 Theorie 1 Theory 1 Two-way two-mode data 1 Ultrametric 1 Visualisierung 1 Visualization 1 Wettbewerb 1 additive trees 1
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Undetermined 8 Free 1
Type of publication
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Article 9
Type of publication (narrower categories)
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Article in journal 1 Aufsatz in Zeitschrift 1
Language
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Undetermined 8 English 1
Author
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Carroll, J. 2 Wilderjans, Tom 2 Brucker, François 1 Ceulemans, E. 1 Chaturvedi, Anil 1 Corter, James 1 Depril, Dirk 1 Desarbo, Wayne 1 Gély, Alain 1 Hutchinson, J. 1 Lee, Michael D. 1 Mechelen, I. 1 Mechelen, Iven 1 Mungale, Amitabh 1 Ringel, Daniel 1
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Journal of Classification 4 Psychometrika 3 Advances in Data Analysis and Classification 1 Journal of marketing research 1
Source
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RePEc 8 ECONIS (ZBW) 1
Showing 1 - 9 of 9
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Multimarket membership mapping
Ringel, Daniel - In: Journal of marketing research 60 (2023) 2, pp. 237-262
Persistent link: https://www.econbiz.de/10014233880
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The SIMCLAS Model: Simultaneous Analysis of Coupled Binary Data Matrices with Noise Heterogeneity Between and Within Data Blocks
Wilderjans, Tom; Ceulemans, E.; Mechelen, I. - In: Psychometrika 77 (2012) 4, pp. 724-740
In many research domains different pieces of information are collected regarding the same set of objects. Each piece of information constitutes a data block, and all these (coupled) blocks have the object mode in common. When analyzing such data, an important aim is to obtain an overall picture...
Persistent link: https://www.econbiz.de/10010848122
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Lowdimensional Additive Overlapping Clustering
Depril, Dirk; Mechelen, Iven; Wilderjans, Tom - In: Journal of Classification 29 (2012) 3, pp. 297-320
overlapping clustering model. This model implies an overlapping clustering of the objects and a reconstruction of the data, with …. Grasping the additive (overlapping) clustering structure of object by variable data may, however, be seriously hampered in case …
Persistent link: https://www.econbiz.de/10010848623
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Parsimonious cluster systems
Brucker, François; Gély, Alain - In: Advances in Data Analysis and Classification 3 (2009) 3, pp. 189-204
Persistent link: https://www.econbiz.de/10008491574
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An Extraction and Regularization Approach to Additive Clustering
Lee, Michael D. - In: Journal of Classification 16 (1999) 2, pp. 255-281
Additive clustering provides a conceptually simple similarity model which is, nevertheless, capable of accommodating arbitrary similarity structures. The discrete nature of the clusters, coupled with the general flexibility of the model, however, means that the derivation of additive clustering...
Persistent link: https://www.econbiz.de/10010794934
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Pairwise partitioning: A nonmetric algorithm for identifying feature-based similarity structures
Hutchinson, J.; Mungale, Amitabh - In: Psychometrika 62 (1997) 1, pp. 85-117
Persistent link: https://www.econbiz.de/10005603603
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A graph-theoretic method for organizing overlapping clusters into trees, multiple trees, or extended trees
Carroll, J.; Corter, James - In: Journal of Classification 12 (1995) 2, pp. 283-313
Persistent link: https://www.econbiz.de/10004999462
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An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models
Chaturvedi, Anil; Carroll, J. - In: Journal of Classification 11 (1994) 2, pp. 155-170
Persistent link: https://www.econbiz.de/10005757515
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Gennclus: New models for general nonhierarchical clustering analysis
Desarbo, Wayne - In: Psychometrika 47 (1982) 4, pp. 449-475
Persistent link: https://www.econbiz.de/10005758160
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