Time series labeling algorithms based on the K-nearest neighbors' frequencies

Nasibov E., Peker S.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.38, sa.5, ss.5028-5035, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 5
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.eswa.2010.09.147
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.5028-5035
  • Anahtar Kelimeler: Time series, Clustering, FCM, K-nearest neighbor, Bispectral index, CLUSTER VALIDITY, MODEL
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In the current paper, time series labeling task is analyzed and some solution algorithms are presented. In these algorithms, fuzzy c-means clustering, which is one of the unsupervised learning methods, is used to obtain the labels of the time series. Then K-nearest neighborhood (KNN) rule is performed on the labels to obtain more relevant smooth intervals.