The Estimation of Students' Academic Success by Data Mining Methods

Creative Commons License

Goker H., Bülbül H. İ., Irmak E.

12th International Conference on Machine Learning and Applications (ICMLA), Florida, Amerika Birleşik Devletleri, 4 - 07 Aralık 2013, ss.535-539 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/icmla.2013.173
  • Basıldığı Şehir: Florida
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.535-539
  • Anahtar Kelimeler: data mining, classification, feature selection, weka, data warehouse, naive bayes, PERFORMANCE
  • Gazi Üniversitesi Adresli: Evet

Özet

Data mining is a process of getting out useful information from data stacks. One of the most common application areas is to use classification of algorithms that estimate the future events by past experiences. In this context, in order to predict future events, a data warehouse is created by using the background of students which includes demographic, personal, school, and course information of students. On this data warehouse by using classification algorithms, new applications which can make inferences for the future could be developed.