NDLI: Development of evolutionary data mining algorithms and their applications to cardiac disease diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Jenn-Long Liu Yu-Tzu Hsu Chih-Lung Hung
Copyright Year	2012
Description	Author affiliation: Dept. of Information Engineering, I-Shou University, Kaohsiung 84001, Taiwan (Yu-Tzu Hsu) \|\| Dept. of Information Technology, E-Da Hospital, Kaohsiung 82445, Taiwan (Chih-Lung Hung) \|\| Dept. of Information Management, I-Shou University, Kaohsiung 84001, Taiwan (Jenn-Long Liu)
Abstract	This paper presents two kinds of evolutionary data mining (EvoDM) algorithms, termed GA-KM and MPSO-KM, to cluster the dataset of cardiac disease and predict the accuracy of diagnostics. Our proposed GA-KM is a hybrid method that combines a genetic algorithm (GA) and K-means (KM) algorithm, and MPSO-KM is also a hybrid method that combines a momentum-type particle swarm optimization (MPSO) and K-means algorithm. The functions of GA-KM or MPSO-KM are to determine the optimal weights of attributes and cluster centers of clusters that are needed to classify the disease dataset. The dataset, used in this study, includes 13 attributes with 270 instances, which are the data records of cardiac disease. A comparative study is conducted by using C5, Naïve Bayes, K-means, GA-KM and MPSO-KM to evaluate the accuracy of presented algorithms. Our experiments indicate that the clustering accuracy of cardiac disease dataset is significantly improved by using GA-KM and MPSO-KM when compared to that of using K-means only.
Starting Page	1
Ending Page	8
File Size	1170224
Page Count	8
File Format	PDF
ISBN	9781467315104
e-ISBN	9781467315098
e-ISBN	9781467315081
DOI	10.1109/CEC.2012.6256640
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cardiac disease Clustering algorithms Genetic algorithms Heart Data mining Accuracy Prediction algorithms cardiac disease Evolutaionary data mining genetic algorith momentum-type particle swarm optimization K-means algorithm
Content Type	Text
Resource Type	Article

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