An Empirical Comparison of Data Mining Techniques in Medical Databases
Kittipol Wisaeng · International Journal of Computer Applications · 2013
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.