An approach to support education of data mining algorithms

The aim of this article is to describe the design, implementation and evaluation of the educational application to support learning of data mining algorithms. The role of the application is to help students to better understand the algorithms such as Naive Bayes classifier, decision trees and associ...

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Bibliographic Details
Published inSAMI : 2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics : 26-28 January 2017 pp. 000093 - 000098
Main Authors Muchova, M., Paralic, J., Jancus, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2017
Subjects
Algorithm design and analysis
Apriori
association rules
Classification algorithms
Data mining
decision tree algorithm C4.5
Decision trees
Education
educational application
MATLAB
MATLAB GUI
Naive Bayes classifier
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DOI10.1109/SAMI.2017.7880282

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Summary:The aim of this article is to describe the design, implementation and evaluation of the educational application to support learning of data mining algorithms. The role of the application is to help students to better understand the algorithms such as Naive Bayes classifier, decision trees and association rules. The application also includes a test area that allows students to generate and solve different types of tasks on one hand side and teachers provide an effective way to test students without the need for creating custom tests on the other side. Presented application was evaluated from the perspective of students and teachers of the subject Knowledge Discovery, in order to verify the functionality and usability of the application in the real teaching process.
DOI:10.1109/SAMI.2017.7880282