A cluster Analysis for Binary Data Using Genetic Algorithms

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    This research was initially driven by the lack of clustering algorithms that focus on binary data. A promising technique to analyze this type of data, namely Genetic Clustering for Unknown K (GCUK) became the main subject in this research. GCUK was applied to cluster four binary data and there is a presence of an imbalanced data in one of the data sets. The results show that GCUK is an efficient and effective clustering algorithm compared to K-means. The other contribution is the capability of GCUK for clustering the unbalanced data. Standard clustering algorithms cannot simply be applied to this type of data sets as it can cause a misclassification results.

     


  • Keywords


    Binary Data; Clustering; Genetic Algorithms.

  • References


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Article ID: 28174
 
DOI: 10.14419/ijet.v7i4.30.28174




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