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OVWTRE: A program for optimal variable weighting for ultrametric and additive tree fitting

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  • Geert Soete

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  • Geert Soete, 1988. "OVWTRE: A program for optimal variable weighting for ultrametric and additive tree fitting," Journal of Classification, Springer;The Classification Society, vol. 5(1), pages 101-104, March.
    • Handle: RePEc:spr:jclass:v:5:y:1988:i:1:p:101-104
    DOI: 10.1007/BF01901677
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. 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.
    2. Anuj Mehrotra & Joseph Shantz & Michael A. Trick, 2005. "Determining newspaper marketing zones using contiguous clustering," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(1), pages 82-92, February.
    3. Yaling Deng & Shuliang Zou & Daming You, 2018. "Theoretical Guidance on Evacuation Decisions after a Big Nuclear Accident under the Assumption That Evacuation Is Desirable," Sustainability, MDPI, vol. 10(9), pages 1-14, August.
    4. Renato Cordeiro Amorim, 2016. "A Survey on Feature Weighting Based K-Means Algorithms," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 210-242, July.
    5. Renato Amorim, 2015. "Feature Relevance in Ward’s Hierarchical Clustering Using the L p Norm," Journal of Classification, Springer;The Classification Society, vol. 32(1), pages 46-62, April.

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