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An Empirical Comparison of Data Mining Techniques in Medical Databases
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 77 - Number 7 |
| Year of Publication: 2013 |
| Authors: Kittipol Wisaeng |
10.5120/13408-1061
|
Kittipol Wisaeng . An Empirical Comparison of Data Mining Techniques in Medical Databases. International Journal of Computer Applications. 77, 7 ( September 2013), 23-27. DOI=10.5120/13408-1061
Abstract
The application of data mining algorithms requires the use of powerful software tools. As the number of available tools continues to grow, the choice of the most suitable tool becomes increasingly difficult. This paper present the basic data mining techniques i. e. , naive Bayesian tree, RIpple DOwn Rule, naive Bayes and decision tree algorithm J48 for classifying in medical databases. The goal of this paper is to provide a comprehensive of different classifying techniques in data mining. To evaluate the performance of the above techniques recall, precision and accuracy measures are applied.
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