An Effective Method Determining the Initial Cluster Centers for K-means for Clustering Gene Expression Data

Tanir D., Nuriyeva F.

2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Türkiye, 5 - 08 Ekim 2017, ss.751-754 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/ubmk.2017.8093520
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.751-754
  • Anahtar Kelimeler: K-means, Gene Expression, Clustering, Data Mining, Initial Cluster Centers, ALGORITHM
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Clustering is an important tool for analyzing gene expression data. Many clustering algorithms have been proposed for the analysis of gene expression data. In this article we have clustered real life gene expression data via K-Means which is one of clustering algorithms. Also, we have proposed a new method determining the initial cluster centers for K-means. We have compared results of our method with other clustering algorithms. The comparison results show that the K-means algorithm which uses the proposed methods converges to better clustering results than other clustering algorithms.