Application of self-organising maps for data mining with incomplete data sets

被引：45
作者：
Wang, SH [1 ]
机构：
[1] Univ Massachusetts Dartmouth, Charlton Coll Business, Dept Mkt Business Informat Syst, N Dartmouth, MA 02747 USA
来源：
NEURAL COMPUTING & APPLICATIONS | 2003年 / 12卷 / 01期
关键词：
fuzzy clustering; incomplete data; self-organising maps;
D O I：
10.1007/s00521-003-0372-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Self-organising maps (SOM) have become a commonly-used cluster analysis technique in data mining. However, SOM are not able to process incomplete data. To build more capability of data mining for SOM, this study proposes an SOM-based fuzzy map model for data mining with incomplete data sets. Using this model, incomplete data are translated into fuzzy data, and are used to generate fuzzy observations. These fuzzy observations, along with observations without missing values, are then used to train the SOM to generate fuzzy maps. Compared with the standard SOM approach, fuzzy maps generated by the proposed method can provide more information for knowledge discovery.
引用
收藏
页码：42 / 48
页数：7
相关论文
共 50 条
  • [1] Application of self-organising maps for data mining with incomplete data sets
    S. Wang
    Neural Computing & Applications, 2003, 12 : 42 - 48
  • [2] Visual data mining with self-organising maps for ventricular fibrillation analysis
    Rosado-Munoz, Alfredo
    Martinez-Martinez, Jose M.
    Escandell-Montero, Pablo
    Soria-Olivas, Emilio
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2013, 111 (02) : 269 - 279
  • [3] The application of self-organising maps to performance analysis data in rugby union
    Croft, Hayden
    Lamb, Peter
    Middlemas, Simon
    INTERNATIONAL JOURNAL OF PERFORMANCE ANALYSIS IN SPORT, 2015, 15 (03) : 1037 - 1046
  • [4] On the Use of Self-Organising Maps to Analyse Spectral Data
    Cariou, Veronique
    Bertrand, Dominique
    ADVANCES IN DATA ANALYSIS: THEORY AND APPLICATIONS TO RELIABILITY AND INFERENCE, DATA MINING, BIOINFORMATICS, LIFETIME DATA, AND NEURAL NETWORKS, 2010, : 267 - +
  • [5] Ecotoxicity and chemical sediment data classification by the use of self-organising maps
    Tsakovski, Stefan
    Kudiak, Blazei
    Simeonov, Vasil
    Wolska, Lidia
    Namiesnik, Jacek
    ANALYTICA CHIMICA ACTA, 2009, 631 (02) : 142 - 152
  • [6] A proposal for direct-ordering gene expression data by self-organising maps
    Gomes, LDCT
    Von Zuban, FJ
    Moscato, P
    APPLIED SOFT COMPUTING, 2004, 5 (01) : 11 - 21
  • [7] Enhancement of topology preservation and hierarchical dynamic self-organising maps for data visualisation
    Hsu, AL
    Halgamuge, SK
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2003, 32 (2-3) : 259 - 279
  • [8] Self-Organising Maps for Image Segmentation
    Wehrens, Ron
    ADVANCES IN DATA ANALYSIS, DATA HANDLING AND BUSINESS INTELLIGENCE, 2010, : 373 - 383
  • [9] Kernel self-organising maps for classification
    Lau, K. W.
    Yin, H.
    Hubbard, S.
    NEUROCOMPUTING, 2006, 69 (16-18) : 2033 - 2040
  • [10] Adapting to Increasing Data Availability using Multi-Layered Self-Organising Maps
    Smith, Toby
    PROCEEDINGS 2009 INTERNATIONAL CONFERENCE ON ADAPTIVE AND INTELLIGENT SYSTEMS, ICAIS 2009, 2009, : 108 - 113
12345