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A novel fuzzy clustering algorithm with between-cluster information for categorical data

  • Published:2013-03 Issue: Volume:215 Page:55-73
  • ISSN:0165-0114
  • Container-title:Fuzzy Sets and Systems
  • language:en
  • Short-container-title:Fuzzy Sets and Systems

Author:

Bai Liang,Liang Jiye,Dang Chuangyin,Cao Fuyuan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Logic

Reference36 articles.

1. Finding localized associations in market basket data;Aggarwal;IEEE Trans. Knowl. Data Eng.,2002

2. Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins;Baxevanis,2001

3. Applications of Data Mining in Computer Security;Barbara,2002

4. A novel attribute weighting algorithm for clustering high-dimensional categorical data;Bai;Pattern Recogn.,2011

5. An initialization method to simultaneously find initial cluster centers and the number of clusters for clustering categorical data;Bai;Knowl-Based Syst.,2011

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1. The DRk-M for Clustering Categorical Datasets With Uncertainty;IEEE Intelligent Systems;2021-09-01

2. A rough set based algorithm for updating the modes in categorical clustering;International Journal of Machine Learning and Cybernetics;2021-03-27

3. Uncertainty mode selection in categorical clustering using the rough set theory;Expert Systems with Applications;2020-11

4. Categorical fuzzy entropy c-means;2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE);2020-07

5. Clustering Categorical Data: A Survey;International Journal of Information Technology & Decision Making;2020-01
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