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

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

Künye