Parameter Selection in Fuzzy Joint Points Clustering Algorithms

Nasibov E., ATILGAN C.

9th International Conference of Information and Communiation Technologies (AICT), Rostov-on-Don, Rusya, 14 - 16 Ekim 2015, ss.8-11 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icaict.2015.7338505
  • Basıldığı Şehir: Rostov-on-Don
  • Basıldığı Ülke: Rusya
  • Sayfa Sayıları: ss.8-11
  • Anahtar Kelimeler: Clustering, Fuzzy logic, Fuzzy joint points
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Applying fuzzy logic to clustering techniques leads to more robust and autonomous methods like the fuzzy joint points (FJP) which is a density based fuzzy clustering algorithm that requires no parameters to be set. However, a straightforward implementation of the method is rather slow. Recently, a faster but parameter dependent version of the algorithm was proposed and a theoretical bound on the parameter was given so that the algorithm produces the exact same results with the original FJP method. In this work, we investigate the tightness of the bound in practice and analyze the effect of the data distribution on the parameter selection problem of the fuzzy joint points clustering.