New Method Based on Rough Set for Filling Missing Value

Cekik R., Telceken S.

6th World Conference on Soft Computing, California, Amerika Birleşik Devletleri, 22 - 25 Mayıs 2016, cilt.361, ss.41-48 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 361
  • Doi Numarası: 10.1007/978-3-319-75408-6_4
  • Basıldığı Şehir: California
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.41-48
  • Anahtar Kelimeler: Missing value, Rough set, Data mining
  • Anadolu Üniversitesi Adresli: Evet

Özet

The presence of missing value in a dataset can affect the performance of an analysis system such as classifier. To solve this problem many methods have been proposed in different studies using different theorems, analysis systems and methods such as Neural Network (NN), k-Nearest Neighbor (k-NN), closest fit etc. In this paper, we propose novel method based on RST for solving the problem of missing value that was lost (e.g., was erased). After dataset filling with proposed method, it has been observed improvement the performance of used analysis systems.