Scopus
YÖKSİS Eşleşti
Extracting rules for classification problems: AIS based approach
Expert Systems with Applications · Eylül 2009
YÖKSİS Kayıtları
Extracting rules for classi cation problems AIS based approach
Expert Systems with Applications · 2009 SCI-Expanded
PROFESÖR HUMAR KAHRAMANLI ÖRNEK →
Makale Bilgileri
DergiExpert Systems with Applications
Yayın TarihiEylül 2009
Cilt / Sayfa36 · 10494-10502
Scopus ID2-s2.0-67349236666
Özet
Although Artificial Neural Network (ANN) usually reaches high classification accuracy, the obtained results in most cases may be incomprehensible. This fact is causing a serious problem in data mining applications. The rules that are derived from ANN are needed to be formed to solve this problem and various methods have been improved to extract these rules. In our previous work, a hybrid neural network was presented for classification (Kahramanli & Allahverdi, 2008). In this study a method that uses Artificial Immune Systems (AIS) algorithm has been presented to extract rules from trained hybrid neural network. The data were obtained from the University of California at Irvine (UCI) machine learning repository. The datasets are Cleveland heart disease and Hepatitis data. The proposed method achieved accuracy values 96.4% and 96.8% for Cleveland heart disease dataset and Hepatitis dataset respectively. It is been observed that these results are one of the best results comparing with results obtained from related previous studies and reported in UCI web sites. © 2009.
Yazarlar (2)
1
Humar Kahramanli
2
Novruz Allahverdi
Anahtar Kelimeler
Artificial Immune Systems
Hybrid neural networks
Opt-aiNET
Optimization
Rule extraction
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
41
Atıf
2
Yazar
5
Anahtar Kelime