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A computationally efficient approximation to the nearest neighbor interchange metric

Author

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  • Edward Brown
  • William Day

Abstract

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Suggested Citation

  • Edward Brown & William Day, 1984. "A computationally efficient approximation to the nearest neighbor interchange metric," Journal of Classification, Springer;The Classification Society, vol. 1(1), pages 93-124, December.
    • Handle: RePEc:spr:jclass:v:1:y:1984:i:1:p:93-124
    DOI: 10.1007/BF01890118
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    References listed on IDEAS

    as
    1. Day, William H. E., 1981. "The complexity of computing metric distances between partitions," Mathematical Social Sciences, Elsevier, vol. 1(3), pages 269-287, May.
    2. Boland, Ralph P. & Brown, Edward K. & Day, William H. E., 1983. "Approximating minimum-length-sequence metrics: a cautionary note," Mathematical Social Sciences, Elsevier, vol. 4(3), pages 261-270, July.
    3. Jarvis, J. P. & Luedeman, J. K. & Shier, D. R., 1983. "Counterexamples in measuring the distance between binary trees," Mathematical Social Sciences, Elsevier, vol. 4(3), pages 271-274, July.
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    Citations

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    Cited by:

    1. Douglas L. Steinley, 2016. "Editorial," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 167-170, July.
    2. Mirko Křivánek, 1986. "Computing the nearest neighbor interchange metric for unlabeled binary trees is NP-complete," Journal of Classification, Springer;The Classification Society, vol. 3(1), pages 55-60, March.
    3. Bock, Hans H., 1996. "Probabilistic models in cluster analysis," Computational Statistics & Data Analysis, Elsevier, vol. 23(1), pages 5-28, November.

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