prikaz prve stranice dokumenta Impact of missing values on the performance of machine learning algorithms
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Scientific paper - Original scientific paper
Impact of missing values on the performance of machine learning algorithms
In: CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023). Tirana: University of Tirana, Faculty of Natural Sciences, Department of Informatics, 2023. pp. 54-62. urn:nbn:hr:277:483201
Radišić, Bojan; Seljan, Sanja; Dunđer, Ivan

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Radišić, B., Seljan, S. & Dunđer, I. (2023). Impact of missing values on the performance of machine learning algorithms. CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023) (pp. 54-62). Tirana: University of Tirana, Faculty of Natural Sciences, Department of Informatics. Retrieved from https://urn.nsk.hr/urn:nbn:hr:277:483201

Radišić, Bojan, et al. "Impact of missing values on the performance of machine learning algorithms." CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023), University of Tirana, Faculty of Natural Sciences, Department of Informatics, 2023, pp. 54-62. https://urn.nsk.hr/urn:nbn:hr:277:483201

Radišić, Bojan, Sanja Seljan and Ivan Dunđer. "Impact of missing values on the performance of machine learning algorithms." In CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023), 54-62. Tirana: University of Tirana, Faculty of Natural Sciences, Department of Informatics, 2023. Accessed 2024 May 24. https://urn.nsk.hr/urn:nbn:hr:277:483201

Radišić, B., Seljan, S. and Dunđer, I. (2023) 'Impact of missing values on the performance of machine learning algorithms', CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023), University of Tirana, Faculty of Natural Sciences, Department of Informatics, Tirana, pp. 54-62. Available at: https://urn.nsk.hr/urn:nbn:hr:277:483201 (Accessed 24 May 2024)

Radišić B, Seljan S, Dunđer I. Impact of missing values on the performance of machine learning algorithms. CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023). Tirana: University of Tirana, Faculty of Natural Sciences, Department of Informatics; 2023. Pp. 54-62. [cited 2024 May 24] Available at: https://urn.nsk.hr/urn:nbn:hr:277:483201

B. Radišić, S. Seljan and I. Dunđer, "Impact of missing values on the performance of machine learning algorithms", CEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023) Tirana: University of Tirana, Faculty of Natural Sciences, Department of Informatics, 2023. [Online] Available at: https://urn.nsk.hr/urn:nbn:hr:277:483201 [Accessed: 24 May 2024]

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Metadata
Title (english)Impact of missing values on the performance of machine learning algorithms
AuthorBojan Radišić
AuthorSanja Seljan
AuthorIvan Dunđer
Author's institutionJosip Juraj Strossmayer University of Osijek
Faculty of Tourism and Rural Development in Pozega
Author's institutionUniversity of Zagreb
Faculty of Humanities and Social Sciences
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract (english)
Machine learning (ML) can be used to analyze and predict student success outcome in order to avoid various problems and to plan future actions for helping students overcome difficulties during their study. This paper analyzes data from a digital system of 309 students who were enrolled in the Specialist Study in Trade Business at the Faculty of Tourism and Rural Development from 2010 to 2018. The paper explores the impact of four different data sets on the performance of ML algorithms. The first data set is with partially missing data on the length of study (around 7%), the second one uses arithmetic means in place of missing data, the third is based on median values, whereas the fourth uses the geometric mean instead. Four popular ML algorithms were considered: k-Nearest Neighbors (KNN), Naïve Bayes (NB), Random Forest (RF) and Probabilistic Neural Network (PNN). All of them are used for predicting student success based on achieved ECTS credit points. The aim of this paper is to compare and analyze the impact of missing values on the results of individual ML algorithms.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Publication titleCEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023)
Numberingpp. 54-62
p-ISSN1613-0073
e-ISSN1613-0073
URN:NBNurn:nbn:hr:277:483201
Publication2023
ConferenceTitle: 5th International Conference on Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT)
Location: Tirana, Albania
Start date: 2023-04-26
End date: 2023-04-27
Assembly type: Lecture
Document URLhttps://ceur-ws.org/Vol-3402/paper07.pdf
Type of resourceText
PublisherUniversity of Tirana, Faculty of Natural Sciences, Department of Informatics
Publishing placeTirana
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
RepositoryFTRR Repository
Created on2023-10-13 07:54:05