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master's thesis
Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:990317
Maljić, Matija
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Maljić, M. (2019). Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:990317

Maljić, Matija. "Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:990317

Maljić, Matija. "Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:990317

Maljić, M. (2019). 'Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 15 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:990317

Maljić M. Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 June 15] Available at: https://urn.nsk.hr/urn:nbn:hr:168:990317

M. Maljić, "Analiza tokova velikih podataka uz pomoć metoda nenadziranog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:990317

Metadata
TitleAnaliza tokova velikih podataka uz pomoć metoda nenadziranog učenja
Title (english)Analysing Big Data Streams Using Unsupervised Learning Methods
AuthorMatija Maljić
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberZoran Skočir (član povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-02-22, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad obrađuje primjenu algoritama strojnog učenja nad tokovima podataka za dubinsku analizu podataka. Prvo je dana definicija strojnog učenja. Definirane su različite vrste strojnog učenja i njihove razlike. Dodatno je objašnjeno nenadzirano učenje, odnosno grupiranje podataka. Zatim su definirani tokovi podataka, objašnjena njihova ograničenja pri rađenju analize i opisana moguća rješenja za primjenu algoritma grupiranja nad njima. Opisana je važnost telekomunikacija, definirane telekomunikacijske prijevare i objašnjeno je kako ih se algoritmima strojnog učenje mogu otkriti. U konačnici implementiran je E-Stream algoritam grupiranja tokova podataka i evaluiran nad sintetičkim skupom podataka.
Abstract (english)
This thesis deals with using machine learning on data streams for data analysis. Firstly, the definition of machine learning is given. Then explained differences between different types of machine learning. Additionally unsupervised learning and clustering was explained. Then data streams are defined, explained their limitations in the data analysis and described possible solutions for applying the clustering algorithms on them. After that, importance of telecommunications is explained, telecommunication fraud is defined and it is explained how frauds could be detected using machine learning algorithms. Finally, E-Stream algorithm for clustering data streams is implemented and evaluated using synthetic dataset.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:990317
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2019-03-13 22:32:57