Scopus
A new approach to classification rule extraction problem by the real value coding
International Journal of Innovative Computing, Information and Control · Eylül 2012
Makale Bilgileri
DergiInternational Journal of Innovative Computing, Information and Control
Yayın TarihiEylül 2012
Cilt / Sayfa8 · 6303-6315
Scopus ID2-s2.0-84866043699
Özet
In this study a new method that uses artificial immune system (AIS) algorithm has been presented to extract rules from medical related dataset. Four real life problems data were investigated for determining feasibility of the proposed method. The data were obtained from machine learning repository of University of California at Irvine (UCI). The datasets were obtained from Iris Dataset which is the multi-class problem, Pima Indian Diabetes Dataset and two different Wisconsin Breast Cancer datasets. The proposed method achieved prediciton accuracy ratios of 100%, 77.2%, 98.54% and 95.61% for the Iris, Pima Indians Diabetes, Wisconsin Breast Cancer (original) and Wisconsin Breast Cancer (diagnostic) datasets, respectively. It has been observed that these results are better than the results obtained from related previous studies. © 2012 ICIC International.
Yazarlar (3)
1
Murat Koklu
ORCID: 0000-0002-2737-2360
2
Humar Kahramanli
3
Novruz Allahverdi
Anahtar Kelimeler
Artificial immune systems
CLONALG algorithm
Rules extraction
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
9
Atıf
3
Yazar
3
Anahtar Kelime