Advanced data preprocessing using fuzzy clustering techniques

被引：9
|
作者：
Genther, H
Glesner, M
机构：
[1] Darmstadt University of Technology, Institute of Microelectronic Systems, 64283 Darmstadt
来源：
FUZZY SETS AND SYSTEMS | 1997年 / 85卷 / 02期
关键词：
fuzzy logic; pattern recognition; data preprocessing; cluster analysis;
D O I：
10.1016/0165-0114(95)00358-4
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper we describe a method of advanced data preprocessing for pattern classification using a fuzzy classification system (FCS). Input pattern vectors are transformed using a matrix before classification to improve classification results and to simplify the FCS. The transformation matrix is calculated using the prototypes obtained with fuzzy clustering methods. The data preprocessed in this way are often classifiable more easily than the original data. Results obtained with the new method using artificially created data and the well-known Iris data set are presented.
引用
收藏
页码：155 / 164
页数：10
相关论文
共 50 条
  • [41] Ensemble imbalance classification: Using data preprocessing, clustering algorithm and genetic algorithm
    Abolkarlou, Niloofar Afshari
    Niknafs, Ali Akbar
    Ebrahimpour, Mohammad Kazem
    [J]. 2014 4TH INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE), 2014, : 171 - 176
  • [42] Multivariate techniques for preprocessing noisy data for source separation using ICA
    P. Ramesh Babu
    Shankar Narasimhan
    [J]. International Journal of Advances in Engineering Sciences and Applied Mathematics, 2012, 4 (1-2) : 32 - 40
  • [43] Traffic Flow Data Mining and Evaluation Based on Fuzzy Clustering Techniques
    Hu Chunchun
    Luo Nianxue
    Yan Xiaohong
    Shi Wenzhong
    [J]. INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2011, 13 (04) : 344 - 349
  • [44] Management zones delineation using fuzzy clustering techniques in grapevines
    Tagarakis, A.
    Liakos, V.
    Fountas, S.
    Koundouras, S.
    Gemtos, T. A.
    [J]. PRECISION AGRICULTURE, 2013, 14 (01) : 18 - 39
  • [45] Streamflow forecasting using neural networks and fuzzy clustering techniques
    Luna, I
    Soares, S
    Magalhaes, MH
    Ballini, R
    [J]. PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5, 2005, : 2631 - 2636
  • [46] Fault location in distribution networks using fuzzy clustering techniques
    Sabry, MM
    Mahmoud, MS
    [J]. ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2001, 9 (02): : 77 - 81
  • [47] Stabilisation diagrams: Pole identification using fuzzy clustering techniques
    Scionti, M
    Lanslots, JP
    [J]. ADVANCES IN ENGINEERING SOFTWARE, 2005, 36 (11-12) : 768 - 779
  • [48] Sit-To-Stand Detection Using Fuzzy Clustering Techniques
    Banerjee, Tanvi
    Keller, James M.
    Skubic, Marjorie
    Abbott, Carmen
    [J]. 2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010), 2010,
  • [49] FUZZY QUERY-PROCESSING USING CLUSTERING-TECHNIQUES
    KAMEL, M
    HADFIELD, B
    ISMAIL, M
    [J]. INFORMATION PROCESSING & MANAGEMENT, 1990, 26 (02) : 279 - 293
  • [50] Management zones delineation using fuzzy clustering techniques in grapevines
    A. Tagarakis
    V. Liakos
    S. Fountas
    S. Koundouras
    T. A. Gemtos
    [J]. Precision Agriculture, 2013, 14 : 18 - 39
12345