prikaz prve stranice dokumenta Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI
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undergraduate thesis
Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI
2020. urn:nbn:hr:168:412589
Sušilović, Martina
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Sušilović, M. (2020). Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:412589

Sušilović, Martina. "Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:412589

Sušilović, Martina. "Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:412589

Sušilović, M. (2020). 'Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:412589

Sušilović M. Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 April 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:412589

M. Sušilović, "Otkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:412589

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Metadata
TitleOtkrivanje stršećih vrijednosti u podatcima uporabom platforme ELKI
Title (english)Detection of Data Outliers Using ELKI Platform
AuthorMartina Sušilović
MentorAlan Jović (mentor)
Committee memberAlan Jović (predsjednik povjerenstva)
Committee memberNikolina Frid (član povjerenstva)
Committee memberIgor Stančin (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Stršećim vrijednostima u podacima smatraju se opažanja koja po nekim svojstvima odstupaju od većine ostalih u skupu. Otkrivanje stršećih vrijednosti važan je postupak u dubinskoj analizi podataka korišten pri otkrivanju zloupotrebe platnih kartica, u medicinskoj dijagnostici, u sigurnosnim sustavima i brojnim drugim područjima. ELKI kao platforma otvorenog koda pruža implementaciju niza algoritama za grupiranje i detekciju anomalija. U ovom završnom radu dan je pregled najpopularnijih metoda za otkrivanje stršećih vrijednosti implementiranih unutar platforme ELKI temeljenih na udaljenosti, dubini, devijaciji, gustoći, itd., pri čemu su opisani principi rada, prednosti i nedostatci, specifičnosti i domene primjene pojedinih algoritama.
Abstract (english)
Outliers are defined as data points that differ significantly from other points in the data set. Outlier detection is an important procedure in data mining used in credit fraud detection, healthcare, etc. ELKI is an open source software containing algorithms for clustering and outlier detection. In this Bachelor thesis, an overview of some of the most popular approaches to outlier detection implemented in ELKI is provided, which also gives insight into each method's principles, advantages and downsides, as well as it's particulars and field of use.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:412589
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 on2023-01-14 09:59:25