An Expert Sytem for Diagnosis Breast Cancer based on Principal Component Analysis Method - Karabatak, Murat; Ince, M. Cevdet; Avci, Engin (Ieee, 2008)
This paper presents an expert diagnosis system for detecting breast cancer based on Principle Component Analysis (PCA). In this study PCA is used for reducing the dimension of breast cancer database and Adaptive Network Based Fuzzy Inference System (ANFIS) and Artitifical Neural Network (ANN) are used for intelligent classification respectively. In there, PCA-ANN system performance is compared with PCA-ANFIS. The dimension of input feature space is reduced from nine to four by using PCA. In test stage, 3-fold cross validation method was applied to the Wisconsin breast cancer database to evaluate the proposed systems performances. The correct classification rates of proposed systems are 97.2% and 95.3% for PCA-YSA and PCA-ANFIS respectively.
Gö?üs kanseri i?çin temel bileşen analiz yöntemi tabanli uzman teşhis sistemi
IEEE 16th Signal Processing and Communications Applications Conference -- APR 20-22, 2008 -- Aydin, TURKEY
Keywords: Principle Component Analysis; Adaptive Network; Based Fuzzy Inference System; Artificial Neural Network; Automatic Detection; Breast Cancer