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A variable-selection heuristic for K-means clustering

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  • Michael Brusco
  • J. Cradit

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  • Michael Brusco & J. Cradit, 2001. "A variable-selection heuristic for K-means clustering," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 249-270, June.
    • Handle: RePEc:spr:psycho:v:66:y:2001:i:2:p:249-270
    DOI: 10.1007/BF02294838
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    References listed on IDEAS

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    1. Geert Soete & Wayne DeSarbo & J. Carroll, 1985. "Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 173-192, December.
    2. P. (Sundar) Balakrishnan & Martha Cooper & Varghese Jacob & Phillip Lewis, 1994. "A study of the classification capabilities of neural networks using unsupervised learning: A comparison withK-means clustering," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 509-525, December.
    3. Niels Waller & Heather Kaiser & Janine Illian & Mike Manry, 1998. "A comparison of the classification capabilities of the 1-dimensional kohonen neural network with two pratitioning and three hierarchical cluster analysis algorithms," Psychometrika, Springer;The Psychometric Society, vol. 63(1), pages 5-22, March.
    4. Wayne DeSarbo & J. Carroll & Linda Clark & Paul Green, 1984. "Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables," Psychometrika, Springer;The Psychometric Society, vol. 49(1), pages 57-78, March.
    5. Paul Green & Jonathan Kim & Frank Carmone, 1990. "A preliminary study of optimal variable weighting in k-means clustering," Journal of Classification, Springer;The Classification Society, vol. 7(2), pages 271-285, September.
    6. Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
    7. Geert Soete, 1986. "Optimal variable weighting for ultrametric and additive tree clustering," Quality & Quantity: International Journal of Methodology, Springer, vol. 20(2), pages 169-180, June.
    8. Robert Saltstone & Ken Stange, 1996. "A computer program to calculate Hubert and Arabie's adjusted rand index," Journal of Classification, Springer;The Classification Society, vol. 13(1), pages 169-172, March.
    9. E. Fowlkes & R. Gnanadesikan & J. Kettenring, 1988. "Variable selection in clustering," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 205-228, September.
    10. Glenn Milligan, 1989. "A validation study of a variable weighting algorithm for cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 6(1), pages 53-71, December.
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    Citations

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    Cited by:

    1. Guan-Hua Huang & Su-Mei Wang & Chung-Chu Hsu, 2011. "Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 584-611, October.
    2. Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
    3. 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.
    4. 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.
    5. Stefano Tonellato & Andrea Pastore, 2013. "On the comparison of model-based clustering solutions," Working Papers 2013:05, Department of Economics, University of Venice "Ca' Foscari".
    6. 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.
    7. Thomas Reutterer & Kurt Hornik & Nicolas March & Kathrin Gruber, 2017. "A data mining framework for targeted category promotions," Journal of Business Economics, Springer, vol. 87(3), pages 337-358, April.
    8. Santi, Éverton & Aloise, Daniel & Blanchard, Simon J., 2016. "A model for clustering data from heterogeneous dissimilarities," European Journal of Operational Research, Elsevier, vol. 253(3), pages 659-672.
    9. Anzanello, Michel J. & Fogliatto, Flavio S., 2011. "Selecting the best clustering variables for grouping mass-customized products involving workers' learning," International Journal of Production Economics, Elsevier, vol. 130(2), pages 268-276, April.
    10. Moon, Sangkil & Jalali, Nima & Erevelles, Sunil, 2021. "Segmentation of both reviewers and businesses on social media," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    11. Naoto Yamashita & Kohei Adachi, 2020. "A Modified k-Means Clustering Procedure for Obtaining a Cardinality-Constrained Centroid Matrix," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 509-525, July.
    12. Aurora Torrente & Juan Romo, 2021. "Initializing k-means Clustering by Bootstrap and Data Depth," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 232-256, July.
    13. Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 123-131, January.
    14. Krzanowski, Wojtek J. & Hand, David J., 2009. "A simple method for screening variables before clustering microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2747-2753, May.
    15. Douglas L. Steinley, 2016. "Editorial," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 167-170, July.
    16. Gao, Jinxin & Hitchcock, David B., 2010. "James-Stein shrinkage to improve k-means cluster analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(9), pages 2113-2127, September.
    17. Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
    18. Kim De Roover & Eva Ceulemans & Marieke Timmerman & John Nezlek & Patrick Onghena, 2013. "Modeling Differences in the Dimensionality of Multiblock Data by Means of Clusterwise Simultaneous Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 648-668, October.
    19. Michael Brusco & Douglas Steinley, 2015. "Affinity Propagation and Uncapacitated Facility Location Problems," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 443-480, October.
    20. Tom Frans Wilderjans & Eva Gaer & Henk A. L. Kiers & Iven Mechelen & Eva Ceulemans, 2017. "Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 86-111, March.
    21. 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.
    22. Douglas Steinley & Michael Brusco, 2008. "Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 125-144, March.
    23. Douglas Steinley, 2007. "Validating Clusters with the Lower Bound for Sum-of-Squares Error," Psychometrika, Springer;The Psychometric Society, vol. 72(1), pages 93-106, March.
    24. Douglas Steinley & Gretchen Hendrickson & Michael Brusco, 2015. "A Note on Maximizing the Agreement Between Partitions: A Stepwise Optimal Algorithm and Some Properties," Journal of Classification, Springer;The Classification Society, vol. 32(1), pages 114-126, April.

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