Fuzzy rules for ant based clustering algorithm

HIGHLIGHTS

• who: Amira Hamdi et al. from the REGIM-Lab: Research Groups in Intelligent Machines, University of Sfax, ENIS, BP, Sfax, Tunisia, University of, France have published the research: Fuzzy Rules for Ant Based Clustering Algorithm, in the Journal: (JOURNAL)
• what: Solutions that the authors propose in this paper are presented in the following. To find partition for unclassifiable objects (Outliers), the authors propose applying, respectively, 𝐾-means algorithm, 𝐾-medoid algorithm, and FCM algorithm on dataset of Outliers samples. The authors compare FASClass with the 𝐾-means, 𝐾-medoid, FCM, and ASClassi (𝑖=1, 2, 3), using test datasets presented . . .
  

   

  

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