Title :
Determination of classification rules for heart diseases
Author :
Kahramanli, Humar ; Allahverdi, Novruz
Author_Institution :
Teknik Egitim Fak. - Elektron. ve Bilgisayar Egitimi Bolumu, Selcuk Univ., Konya
Abstract :
Although artificial neural network (ANN) usually reaches high classification accuracy, the obtained results sometimes may be incomprehensible. This fact is causing a serious problem in data mining applications. The rules that are derived from ANN are needed to be formed to solve this problem and various methods have been improved to extract these rules. In this study for the purpose of extracting rules from ANN which has been trained for classification has been used OptaiNET that is an artificial immune algorithm (AIS) and a set of rules has been formed for heart diseases. The proposed method is named as OPTBP.
Keywords :
cardiology; data mining; diseases; medical computing; neural nets; pattern classification; OptaiNET; artificial immune algorithm; artificial neural network; classification rule; data mining; heart disease; Artificial neural networks; Cardiac disease; Data mining; Testing;
Conference_Titel :
Signal Processing, Communication and Applications Conference, 2008. SIU 2008. IEEE 16th
Conference_Location :
Aydin
Print_ISBN :
978-1-4244-1998-2
Electronic_ISBN :
978-1-4244-1999-9
DOI :
10.1109/SIU.2008.4632649
