prikaz prve stranice dokumenta Impact of missing values on the performance of machine learning algorithms
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Impact of missing values on the performance of machine learning algorithms
U: 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. str. 54-62. urn:nbn:hr:277:483201
Radišić, Bojan; Seljan, Sanja; Dunđer, Ivan

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Radišić, B., Seljan, S. i 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) (str. 54-62). Tirana: University of Tirana, Faculty of Natural Sciences, Department of Informatics. Preuzeto s 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, str. 54-62. https://urn.nsk.hr/urn:nbn:hr:277:483201

Radišić, Bojan, Sanja Seljan i Ivan Dunđer. "Impact of missing values on the performance of machine learning algorithms." U 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. Citirano 29.04.2024.. https://urn.nsk.hr/urn:nbn:hr:277:483201

Radišić, B., Seljan, S. i 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, str. 54-62. Preuzeto s: https://urn.nsk.hr/urn:nbn:hr:277:483201 (Datum pristupa: 29.04.2024.)

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. Str. 54-62. [pristupljeno 29.04.2024.] Dostupno na: https://urn.nsk.hr/urn:nbn:hr:277:483201

B. Radišić, S. Seljan i 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] Dostupno na: https://urn.nsk.hr/urn:nbn:hr:277:483201 [Citirano: 29.04.2024.]

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Podaci o radu
Naslov (engleski)Impact of missing values on the performance of machine learning algorithms
AutorBojan Radišić
AutorSanja Seljan
AutorIvan Dunđer
Autorova ustanovaSveučilište Josipa Jurja Strossmayera u Osijeku
Fakultet turizma i ruralnog razvoja u Požegi
Autorova ustanovaSveučilište u Zagrebu
Filozofski fakultet
Znanstveno / umjetničko
područje, polje i grana		DRUŠTVENE ZNANOSTI
Informacijske i komunikacijske znanosti
Sažetak (engleski)
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.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov zbornikaCEUR Workshop Proceedings: Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT 2023)
Brojčani podacistr. 54-62
p-ISSN1613-0073
e-ISSN1613-0073
URN:NBNurn:nbn:hr:277:483201
Datum objave publikacije2023
SkupNaziv: 5th International Conference on Recent Trends and Applications in Computer Science and Information Technology (RTA-CSIT)
Lokacija: Tirana, Albanija
Datum početka: 2023-04-26
Datum završetka: 2023-04-27
Vrsta izlaganja: Predavanje
URL dokumentahttps://ceur-ws.org/Vol-3402/paper07.pdf
Vrsta resursaTekst
IzdavačUniversity of Tirana, Faculty of Natural Sciences, Department of Informatics
Mjesto izdavanjaTirana
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Datum i vrijeme pohrane2023-10-13 07:54:05