A new classifier based on attribute weighted artificial immune system (AWAIS)
Yükleniyor...
Tarih
2004
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER-VERLAG BERLIN
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
'Curse of Dimensionality' problem in shape-space representation which is used in many network-based Artificial Immune Systems (AISs) affects classification performance at a high degree. In this paper, to increase classification accuracy, it is aimed to minimize the effect of this problem by developing an Attribute Weighted Artificial Immune System (AWAIS). To evaluate the performance of proposed system, aiNet, an algorithm that have a considerably important place among network-based AIS algorithms, was used for comparison with our developed algorithm. Two artificial data sets used in aiNet, Two-spirals data set and Chainlink data set were applied in the performance analyses, which led the results of classification performance by means of represented network units to be higher than aiNet. Furthermore, to evaluate performance of the algorithm in a real world application, wine data set that taken from UCI Machine Learning Repository is used. For the artificial data sets, proposed system reached 100% classification accuracy with only a few numbers of network units and for the real world data set, wine data set, the algorithm obtained 98.23% classification accuracy which is very satisfying result if it is considered that the maximum classification accuracy obtained with other systems is 98.9%.
Açıklama
19th International Symposium on Computer and Information Sciences (ISCIS 2004) -- OCT 27-29, 2004 -- Kemer Antalya, TURKEY
Anahtar Kelimeler
Kaynak
COMPUTER AND INFORMATION SCIENCES - ISCIS 2004, PROCEEDINGS
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
3280
