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master's thesis
Statističke metode grupiranja u analizi podataka
Zagreb: University of Zagreb, Faculty of Science, 2016. urn:nbn:hr:217:072997
Uremović, Kristina
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Uremović, K. (2016). Statističke metode grupiranja u analizi podataka (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:072997

Uremović, Kristina. "Statističke metode grupiranja u analizi podataka." Master's thesis, University of Zagreb, Faculty of Science, 2016. https://urn.nsk.hr/urn:nbn:hr:217:072997

Uremović, Kristina. "Statističke metode grupiranja u analizi podataka." Master's thesis, University of Zagreb, Faculty of Science, 2016. https://urn.nsk.hr/urn:nbn:hr:217:072997

Uremović, K. (2016). 'Statističke metode grupiranja u analizi podataka', Master's thesis, University of Zagreb, Faculty of Science, accessed 23 December 2024, https://urn.nsk.hr/urn:nbn:hr:217:072997

Uremović K. Statističke metode grupiranja u analizi podataka [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2016 [cited 2024 December 23] Available at: https://urn.nsk.hr/urn:nbn:hr:217:072997

K. Uremović, "Statističke metode grupiranja u analizi podataka", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:217:072997

Metadata
TitleStatističke metode grupiranja u analizi podataka
AuthorKristina Uremović
MentorSiniša Slijepčević (mentor)
Committee memberSiniša Slijepčević (predsjednik povjerenstva)
Committee memberPavle Pandžić (član povjerenstva)
Committee memberGoran Muić (član povjerenstva)
Committee memberIgor Pažanin (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2016-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Kroz ovaj rad smo pobliže objasnili klaster analizu kao i njenu primjenu na podatke jedne bolnice. Upoznali smo se sa osnovnim pojmovima i tehnikama klasterizacije, te mjerama na kojima se podaci spajaju u klastere. Uz to smo objasnili metodu klasterizacije zasnovanu na unaprijed određenom broju klastera koju smo primijenili na dane podatke. Klaster analiza podrazumijeva klasifikaciju i prepoznavanje strukture. Traži se optimalna struktura podataka za grupiranje opažanja u klastere koji se formiraju na temelju dostupnih informacija koje opisuju podatke i njihove veze. Cilj je pronaći optimalan kriterij grupiranja kod kojeg su opažanja unutar svakog klastera slična, ali se različiti klasteri međusobno razlikuju. Analizirali smo podatke o pregledima u određenoj bolnici. Primjenom klaster analize, uočili smo različite klastere koji povezuju tipove pregleda s raznim karakteristikama pacijenata, poput spola.
Abstract (english)
Through this dissertation, we have shown how one can use cluster analysis methods in medicine. We met the basic concepts of cluster analysis: definition, clustering methods and measures for forming clusters. In addition we explained the method by which we process the given data. Cluster analysis includes the classification and identification of structures. It looks for optimal structure of the given data and then forms clusters based on the information about the data. The goal is to find the optimal grouping criteria in which the observations within each cluster are similar, a different clusters differ from each other. We analyzed data on examinations in a certain hospital. By applying cluster analysis, we identified different clusters which relate different types of examination with characteristics of patients, such as sex.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:072997
Study programmeTitle: Finance and Business Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-02-18 11:55:22