Using Classification On Upisi Database

Kjiroski, Kiril and Kostoska, Magdalena (2010) Using Classification On Upisi Database. In: Proceedings of the Seventh Conference on Informatics and Information Technology. Institute of Informatics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University in Skopje, Macedonia, Skopje, Macedonia, pp. 59-64. ISBN 978-9989-668-88-3

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Abstract

Data mining plays a big role when analyzing data gathered over a period of time. It helps make sense out of a big collection of records, called dataset. Classification is one of the most common techniques of data mining, which occurs very frequently in everyday life. Classification involves diving up objects so that each of these objects will fall into one of mutually exhaustive and exclusive categories we call classes. In this paper, it will be discussed some of the most frequently used classification methods. These methods will be tested on a chosen dataset to serve as an example of which of these methods is most suitable for such dataset form. The dataset is extracted from Application "Upisi", and treated with three classification approaches: Naive Bayes, Nearest Neighbor and Decision Trees.

Item Type: Book Section
Subjects: International Conference on Informatics and Information Technologies > eWorld - eWork, eCommerce, eBusiness, eLearning
Depositing User: Vangel Ajanovski
Date Deposited: 28 Oct 2016 00:15
Last Modified: 28 Oct 2016 00:15
URI: http://eprints.finki.ukim.mk/id/eprint/11154

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