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Clustering objects on subsets of attributes (with discussion)

Citations

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Cited by:

  1. Peter D. Hoff, 2005. "Subset Clustering of Binary Sequences, with an Application to Genomic Abnormality Data," Biometrics, The International Biometric Society, vol. 61(4), pages 1027-1036, December.
  2. Lian, Heng, 2010. "Sparse Bayesian hierarchical modeling of high-dimensional clustering problems," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1728-1737, August.
  3. Benhuai Xie & Wei Pan & Xiaotong Shen, 2008. "Variable Selection in Penalized Model‐Based Clustering Via Regularization on Grouped Parameters," Biometrics, The International Biometric Society, vol. 64(3), pages 921-930, September.
  4. Yang, Aijun & Jiang, Xuejun & Liu, Pengfei & Lin, Jinguan, 2016. "Sparse Bayesian multinomial probit regression model with correlation prior for high-dimensional data classification," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 241-247.
  5. Beibei Yuan & Willem Heiser & Mark Rooij, 2019. "The δ-Machine: Classification Based on Distances Towards Prototypes," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 442-470, October.
  6. Sfyridis, Alexandros & Agnolucci, Paolo, 2020. "Annual average daily traffic estimation in England and Wales: An application of clustering and regression modelling," Journal of Transport Geography, Elsevier, vol. 83(C).
  7. Ronglai Shen & Qianxing Mo & Nikolaus Schultz & Venkatraman E Seshan & Adam B Olshen & Jason Huse & Marc Ladanyi & Chris Sander, 2012. "Integrative Subtype Discovery in Glioblastoma Using iCluster," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-9, April.
  8. Francisco de A. T. Carvalho & Antonio Irpino & Rosanna Verde & Antonio Balzanella, 2022. "Batch Self-Organizing Maps for Distributional Data with an Automatic Weighting of Variables and Components," Journal of Classification, Springer;The Classification Society, vol. 39(2), pages 343-375, July.
  9. Arias-Castro, Ery & Pu, Xiao, 2017. "A simple approach to sparse clustering," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 217-228.
  10. Tsai, Chieh-Yuan & Chiu, Chuang-Cheng, 2008. "Developing a feature weight self-adjustment mechanism for a K-means clustering algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4658-4672, June.
  11. Gaynor, Sheila & Bair, Eric, 2017. "Identification of relevant subtypes via preweighted sparse clustering," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 139-154.
  12. Daniel B. McArtor & Gitta H. Lubke & C. S. Bergeman, 2017. "Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1052-1077, December.
  13. Zhaoyu Xing & Yang Wan & Juan Wen & Wei Zhong, 2024. "GOLFS: feature selection via combining both global and local information for high dimensional clustering," Computational Statistics, Springer, vol. 39(5), pages 2651-2675, July.
  14. Susan Brudvig & Michael J. Brusco & J. Dennis Cradit, 2019. "Joint selection of variables and clusters: recovering the underlying structure of marketing data," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(1), pages 1-12, March.
  15. Grn, Bettina & Leisch, Friedrich, 2009. "Dealing with label switching in mixture models under genuine multimodality," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 851-861, May.
  16. Jian Guo & Elizaveta Levina & George Michailidis & Ji Zhu, 2010. "Pairwise Variable Selection for High-Dimensional Model-Based Clustering," Biometrics, The International Biometric Society, vol. 66(3), pages 793-804, September.
  17. Maarten M. Kampert & Jacqueline J. Meulman & Jerome H. Friedman, 2017. "rCOSA: A Software Package for Clustering Objects on Subsets of Attributes," Journal of Classification, Springer;The Classification Society, vol. 34(3), pages 514-547, October.
  18. Cathy Maugis & Gilles Celeux & Marie-Laure Martin-Magniette, 2009. "Variable Selection for Clustering with Gaussian Mixture Models," Biometrics, The International Biometric Society, vol. 65(3), pages 701-709, September.
  19. Sijian Wang & Ji Zhu, 2008. "Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data," Biometrics, The International Biometric Society, vol. 64(2), pages 440-448, June.
  20. Binder Harald & Müller Tina & Schwender Holger & Golka Klaus & Steffens Michael & Hengstler Jan G. & Ickstadt Katja & Schumacher Martin, 2012. "Cluster-Localized Sparse Logistic Regression for SNP Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-31, August.
  21. Banerjee, Trambak & Mukherjee, Gourab & Radchenko, Peter, 2017. "Feature screening in large scale cluster analysis," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 191-212.
  22. Floriello, Davide & Vitelli, Valeria, 2017. "Sparse clustering of functional data," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 1-18.
  23. Nicoleta Serban, 2008. "Estimating and clustering curves in the presence of heteroscedastic errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(7), pages 553-571.
  24. Galimberti, Giuliano & Soffritti, Gabriele, 2007. "Model-based methods to identify multiple cluster structures in a data set," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 520-536, September.
  25. Nikulin, V., 2006. "Threshold-based clustering with merging and regularization in application to network intrusion detection," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1184-1196, November.
  26. Ioana Manafi & Daniela Marinescu & Monica Roman & Karen Hemming, 2017. "Mobility in Europe: Recent Trends from a Cluster Analysis," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(46), pages 711-711, August.
  27. Selinski, Silvia, 2006. "Similarity Measures for Clustering SNP and Epidemiological Data," Technical Reports 2006,25, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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