Assessment of Association Rules based on Certainty Factor: an Application on Heart Data Set

Akbas K. E., Kivrak M., ARSLAN A., ÇOLAK C.

International Conference on Artificial Intelligence and Data Processing (IDAP), Malatya, Türkiye, 21 - 22 Eylül 2019 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/idap.2019.8875977
  • Basıldığı Şehir: Malatya
  • Basıldığı Ülke: Türkiye
  • İnönü Üniversitesi Adresli: Evet

Özet

Association rules mining is one of the uttermost applied techniques in data mining and artificial intelligence. Support and confidence are two basic measures employed in the evaluation of association rules. The rules obtained with these two values are often correct; however, they are not strong rules. Most of the rules, especially with a high support value, are misleading. For this reason, there are many interestingness measures proposed to achieve stronger rules.