A Meta-heuristic to Generate Rules for the Diagnosis of Heart Disease in Maysan Teaching Hospital Al-Abbas Gesoon J.K.1,* 1M. Sc. Dept. of Computer, Al-Muthanna University, Iraq *Corresponding Author: Gesoon J.K. Al-Abbas, M. Sc. Dept. of Computer, Al-Muthanna University, Iraq, e-mail: ghusoonalabbas@gmail.com
Online published on 23 December, 2019. Abstract One of the most important tasks in data mining development is the classification rule mining which is tried for finding the rules small set of training data set by the objectives that are pre-determined. Disease of Heart leads the millions of death in all over the world. Algorithm of Particle Swarm Optimization (PSO), that has currently appeared as the novel Meta-heuristic achieved of the nature, has absorbed a lot of interests of researchers. Algorithm has been used successfully for some issues of reduction optimization, however, this algorithm usage for the classification rule mining in data mining context still is the area of study that some people have attended for exploring. Diagnosis of heart disease is a progress for predicting, detecting heart disease of medical data of the patient. In the current study, the method of PSO algorithm is used to generate rules for the diagnosis of heart disease in Maysan teaching hospital. The results of experiments showed that the accuracy of proposed method for real data is 77%. Top Keywords Data mining, Particle swarm optimization, Heart disease, Meta-heuristic. Top |