Automatic determination of diseases related to lymph system from lymphography data using principles component analysis (PCA), fuzzy weighting pre-processing and ANFIS
Küçük Resim Yok
Tarih
2007
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
PERGAMON-ELSEVIER SCIENCE LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
It is evident that usage of machine learning methods in disease diagnosis has been increasing gradually. In this study, diagnosis of lymph diseases, which is a very common and important disease, was conducted with such a machine learning system. In this study, we have detected on lymph diseases using principles component analysis (PCA), fuzzy weighting pre-processing and adaptive neuro-fuzzy inference system (ANFIS). The approach system has three stages. In the first stage, dimension of lymph diseases dataset that has 18 features is reduced to four features using principles component analysis. In the second stage, a new weighting scheme based on fuzzy weighting method was utilized as a pre-processing step before the main classifier. Then, in the third stage, ANFIS was our used classifier. We took the lymph diseases dataset used in our study from the UCI machine learning database. The obtained classification accuracy of our system was 88.83% and it was very promising with regard to the other classification applications in the literature for this problem. (c) 2006 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
lymph diseases, PCA, ANFIS, fuzzy weighting pre-processing, expert systems
Kaynak
EXPERT SYSTEMS WITH APPLICATIONS
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
33
Sayı
3