EFFECTIVE ALGORITHMS FOR THE NEAREST-NEIGHBOR METHOD IN THE CLUSTERING PROBLEM

被引：13
|
作者：
HATTORI, K
TORII, Y
机构：
[1] Department of Electrical Engineering and Electronics, Toyohashi University of Technology, Toyohashi, 441, Tempaku-cho
来源：
PATTERN RECOGNITION | 1993年 / 26卷 / 05期
关键词：
AGGLOMERATIVE CLUSTERING; NEAREST NEIGHBOR METHOD; SIMILARITY MATRIX; FUZZY CLUSTERING ALGORITHMS; COMPUTATION TIME;
D O I：
10.1016/0031-3203(93)90127-I
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Two effective algorithms are presented for the nearest neighbor method in the hierarchical agglomerative clustering procedures. One is effective, when the number of clusters into which a data set should be classified is already known. The other is effective to search for several probable clustering solutions, when the number of clusters to be obtained is not known in advance. The computation times of the algorithms are shown to be O(N2) for clustering of N objects. Therefore, the algorithms are very powerful for the nearest neighbor method to classify a large data set.
引用
收藏
页码：741 / 746
页数：6
相关论文
共 50 条
  • [21] Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data
    Fang, Yixiang
    Cheng, Reynold
    Tang, Wenbin
    Maniu, Silviu
    Yang, Xuan
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2016, 28 (03) : 785 - 800
  • [22] NEAREST-NEIGHBOR ALGORITHMS FOR LOAD-BALANCING IN PARALLEL COMPUTERS
    XU, CZ
    LAU, FCM
    MONIEN, B
    LULING, R
    CONCURRENCY-PRACTICE AND EXPERIENCE, 1995, 7 (07): : 707 - 736
  • [23] QUANTUM ALGORITHMS FOR NEAREST-NEIGHBOR METHODS FOR SUPERVISED AND UNSUPERVISED LEARNING
    Wiebe, Nathan
    Kapoor, Ashish
    Svore, Krysta M.
    QUANTUM INFORMATION & COMPUTATION, 2015, 15 (3-4) : 316 - 356
  • [24] Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data
    Fang, Yixiang
    Cheng, Reynold
    Tang, Wenbin
    Maniu, Silviu
    Yang, Xuan
    2016 32ND IEEE INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2016, : 1528 - 1529
  • [25] Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning
    Quantum Architectures and Computation Group, Microsoft Research, One Microsoft Way Redmond, Washington
    98052, United States
    Quantum Inf. Comput., 3-4 (318-358):
  • [26] Fast nearest-neighbor codeword search algorithms for vector quantization
    Sun, Sheng-He
    Lu, Zhe-Ming
    Liu, Chun-He
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2001, 29 (SUPPL.): : 1772 - 1777
  • [27] Protein β-turn prediction using nearest-neighbor method
    Kim, S
    BIOINFORMATICS, 2004, 20 (01) : 40 - 44
  • [28] NearTree, a data structure and a software toolkit for the nearest-neighbor problem
    Andrews, Lawrence C.
    Bernstein, Herbert J.
    JOURNAL OF APPLIED CRYSTALLOGRAPHY, 2016, 49 : 756 - 761
  • [29] Tensored nearest-neighbor classifiers
    Chalasani, V
    Beling, PA
    1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5, 1998, : 2913 - 2916
  • [30] NEAREST-NEIGHBOR CLASSIFIER FOR THE PERCEPTRON
    BOUTEN, M
    VANDENBROECK, C
    EUROPHYSICS LETTERS, 1994, 26 (01): : 69 - 74
12345