A NEW APPROACH TO CLASSIFICATION RULE EXTRACTION PROBLEM BY THE REAL VALUE CODING
Küçük Resim Yok
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ICIC INTERNATIONAL
Erişim Hakkı
info:eu-repo/semantics/closedAccess
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.
Açıklama
Anahtar Kelimeler
Rules extraction, Artificial immune systems, CLONALG algorithm
Kaynak
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
8
Sayı
9
