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master's thesis
KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA
Diplomski rad
2016. urn:nbn:hr:124:131094
Ivanišević, Frane
University of Split
Faculty of economics Split

Cite this document

Ivanišević, F. (2016). KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad (Master's thesis). Split: University of Split, Faculty of economics Split. Retrieved from https://urn.nsk.hr/urn:nbn:hr:124:131094

Ivanišević, Frane. "KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad." Master's thesis, University of Split, Faculty of economics Split, 2016. https://urn.nsk.hr/urn:nbn:hr:124:131094

Ivanišević, Frane. "KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad." Master's thesis, University of Split, Faculty of economics Split, 2016. https://urn.nsk.hr/urn:nbn:hr:124:131094

Ivanišević, F. (2016). 'KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad', Master's thesis, University of Split, Faculty of economics Split, accessed 03 December 2024, https://urn.nsk.hr/urn:nbn:hr:124:131094

Ivanišević F. KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad [Master's thesis]. Split: University of Split, Faculty of economics Split; 2016 [cited 2024 December 03] Available at: https://urn.nsk.hr/urn:nbn:hr:124:131094

F. Ivanišević, "KOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad", Master's thesis, University of Split, Faculty of economics Split, Split, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:124:131094

Metadata
TitleKOMPARATIVNA ANALIZA PREDIKTIVNIH TEHNIKA RUDARENJA PODATAKA : Diplomski rad
AuthorFrane Ivanišević
MentorMario Jadrić (mentor)
MBZ: 292585
GranterUniversity of Split
Faculty of economics Split
Split
Defense date and country2016-09, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Economics
Business Informatics
Abstract
Ovaj rad uspoređuje 4 različite prediktivne tehnike rudarenja podataka na 3 različita skupa podataka.Skupovi podataka su posebni te imaju različite kombinacije karakteristike: broj instanci,broj atributa i broj klasa.Skupovi podataka su predstavljeni i analizirani te iskoršteni za predviđanje klasa. Skupovi podataka preuzeti sa Interneta su čisti i spremni za analizu.Priprema skupova podataka obuhvaćala je samo odabir atributnih podskupova za izgradnju modela.. U teorijskom dijelu rada detaljno je opisano sve od pojma rudarenja podataka do 4 najpopularnija algoritma za klasificiranje klasa.
Abstract (english)
This thesis compares four diffrent predictive data-mining tehniques on three diffrent data set. These data are unique and have diffrent combination of the characteristics: number of instances,number of attributes and number of classes. Data set are introduced ,analyzed and used for class prediction.Data set downloadeded from UCI repository are clean and ready for analysis. Data set preperation includes attribute subset selection for building predictive model.In theoretic part of thesis there is detail description of data-mining proces to 4 most used classification algorithm
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:124:131094
Study programmeTitle: Business Studies
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra ekonomije (magistar/magistra ekonomije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2016-11-10 11:54:44