Epileptic seizure prediction for imbalanced datasets Dengesiz veri kümeleri için epileptik nöbet tahmini

COŞGUN E., ÇELEBİ A., Gullu M. K.

2019 Medical Technologies Congress, TIPTEKNO 2019, İzmir, Türkiye, 3 - 05 Ekim 2019, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/tiptekno.2019.8895137
  • Basıldığı Şehir: İzmir
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: epileptic seizure prediction, imbalanced dataset, rusboost Classifier
  • Kırklareli Üniversitesi Adresli: Evet

Özet

In this study, the methods used in the classification of imbalanced data sets were applied to EEG signals obtained from epilepsy patients and epileptic seizures were estimated. Firstly, the data set was balanced by using under-sampling, oversampling, and synthetic minority over-sampling technique and classified with Support Vector Machines. Then, the data set was classified using the Rusboost classifier without balancing. Classification results were compared with different criteria and the advantages and disadvantage of the methods were evaluated.