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undergraduate thesis
Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:059567
Šarić, Igor
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Šarić, I. (2018). Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:059567

Šarić, Igor. "Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:059567

Šarić, Igor. "Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:059567

Šarić, I. (2018). 'Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 21 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:059567

Šarić I. Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 June 21] Available at: https://urn.nsk.hr/urn:nbn:hr:168:059567

I. Šarić, "Usporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:059567

Metadata
TitleUsporedba uspješnosti različitih algoritama strojnog učenja na različitim skupovima podataka
Title (english)Comparing Efficiency of Various Machine Learning Algorithms on Different Datasets
AuthorIgor Šarić
MentorMarin Šilić (mentor)
Committee memberMarin Šilić (predsjednik povjerenstva)
Committee memberKlemo Vladimir (član povjerenstva)
Committee memberGoran Delač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj je usporediti algoritme strojnog učenja koji rješavaju problem klasifikacije na različitim skupovima podatka. Usporedba se temelji na točnosti predviđanja algoritama na njima prije neviđenim podacima. Algoritmi koji se uspoređuju su: Naivni Bayesov klasifikator, Stablo odluke, Najbliži susjed, Linearna diskriminantna analiza, Logistička regresija i Stroj potpornih vektora. Usporedba se provodila nad tri različita skupa podataka. Rezultati usporedbe su pokazali da algoritmi Stablo odluke i Najbliži susjed imaju dobru točnost neovisno o vrsti podataka, dok algoritmi Linearne diskriminantne analize, Logističke regresije i Stroja potpornih vektora imaju dobre i bolje rezultate za specifičnije vrste podatka.
Abstract (english)
The goal is to compare different machine learning algorithms for classification problems using different datasets. The comparison is based on predicting the classes of data not previously seen by the algorithms. Algorithms used in the comparison are: Naive Bayes classifier, Decision tree, Nearest neighbour, Linear discriminant analysis, Logistic regression, Support vector machine. Three different datasets were used for the comparison. Results of the comparison show that accuracies of Nearest neighbour and Decision tree algorithms are good, no matter the data type, while algorithms like Linear discriminant analysis, Logistic regression and Support vector machine have better result for specific data types.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:059567
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2019-03-14 01:08:25