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Heart Disease Prediction using Genetic Algorithm with Rule Based Classifier in Data Mining

File Size:
953.30 kB
Volume:
Volume 3, Issue 5 (May, 2017)
Publication No:
IJTC201705001
Author:
Megha Shahi, Er. Rupinder Kaur Gurm
Downloads:
12 x

Abstract:
Data mining is a computer based process which analyzes huge set of data for extracting useful patterns or information. Data mining tools provide trends which can occur in future so that knowledge driven decisions can be made by different business organizations. Data mining tools can be used by different business organizations for analyzing the real world problems which take huge time to resolve. During prediction of heart disease huge amount of data is generated which is complex to analyzed using traditional methods.   The data mining provide a methodology to transfer huge set of data into useful information so that knowledge driven decisions can be formed. By using data mining techniques for prediction of heart disease more accurate results can be generated in less time. In this paper a genetic algorithm is proposed for the prediction of heart disease using rule based classifier. As rule based classifier take dataset that contain only important attributes which are fetched by using genetic algorithm. So rule based classifier provide results in the form of Decision Table which provide reliable performance in diagnosing heart disease.

Keywords:
Data mining, Heart disease, Genetic algorithm, Rule based classifier, Classification.