RESEARCH PAPER
Comparative Evaluation of the Different Data Mining Techniques Used for the Medical Database
1
Department of Mechanics and Computer Science, Bialystok University of Technology, ul. Wiejska 45c, 15-351 Bialystok, Poland
Submission date: 2016-02-02
Acceptance date: 2016-07-25
Online publication date: 2016-08-06
Publication date: 2016-09-01
Acta Mechanica et Automatica 2016;10(3):233-238
KEYWORDS
ABSTRACT
Data mining is the upcoming research area to solve various problems. Classification and finding association are two main steps in the field of data mining. In this paper, we use three classification algorithms: J48 (an open source Java implementation of C4.5 algorithm), Multilayer Perceptron - MLP (a modification of the standard linear perceptron) and Naïve Bayes (based on Bayes rule and a set of conditional independence assumptions) of the Weka interface. These classifiers have been used to choose the best algorithm based on the conditions of the voice disorders database. To find association rules over transactional medical database first we use apriori algorithm for frequent item set mining. These two initial steps of analysis will help to create the medical knowledgebase. The ultimate goal is to build a model, which can improve the way to read and interpret the existing data in medical database and future data as well.
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| eISSN: | 2300-5319 |
| ISSN: | 1898-4088 |
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