Using Classification On ISII Database

Kjiroski, Kiril and Kostoska, Magdalena and Madevska-Bogdanova, Ana (2011) Using Classification On ISII Database. In: Proceedings of the Eighth 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. 63-67. ISBN 978-9989-668-90-6

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Abstract

Data mining is the process of applying these methods to data with the intention of uncovering hidden patterns. [1] Classification is one of the most common techniques of data mining, which occurs very frequently in everyday life. Classification is the central data mining technique that we use in this research. Since classification involves diving up objects so that each of these objects will fall into one of mutually exhaustive and exclusive categories we call classes, we use this technique to classify the numbers of enrolment of a student needed to complete a certain course. In this paper, we will be using 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 Neighbour and Decision Trees. Our main goal is to compare the results gain from the database of the application Upisi in 2010 [2] and the results from 2011. Through this comparison we establish how to improve our classification technique.

Item Type: Book Section
Subjects: International Conference on Informatics and Information Technologies > Intelligent Systems
International Conference on Informatics and Information Technologies > Robotics
International Conference on Informatics and Information Technologies > Bioinformatics
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/11155

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