An expert system based on Generalized Discriminant Analysis and Wavelet Support Vector Machine for diagnosis of thyroid diseases - Dogantekin, Esin; Dogantekin, Akif; Avci, Derya (Pergamon-Elsevier Science Ltd, 2011)
Nowadays, there are many persons, which suffer from thyroid diseases. Therefore, the correct diagnosis of these diseases are very important topic. In this study, a Generalized Discriminant Analysis and Wavelet Support Vector Machine System (GDA_WSVM) method for diagnosis of thyroid diseases is presented. This proposed system includes three phases. These are feature extraction feature reduction phase, classification phase, and test of GDA_WSVM for correct diagnosis of thyroid diseases phase, respectively. The correct diagnosis performance of this GDA_WSVM expert system for diagnosis of thyroid diseases is estimated by using classification accuracy and confusion matrix methods, respectively. The classification accuracy of this expert system for diagnosis of thyroid diseases was obtained about 91.86%. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords: Generalized Discriminant Analysis (GDA); Wavelet Support Vector Machine (WSVM) classifier; Thyroid gland; Expert diagnosis system; Classification accuracy; Confusion matrix