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Title:Primerjalna analiza orodij za rudarjenje podatkov : diplomsko delo
Authors:ID Skenderska, Katerina (Author)
ID Nemec Zlatolas, Lili (Mentor) More about this mentor... New window
ID Perša, Tomi (Comentor)
Files:.pdf UN_Skenderska_Katerina_2025.pdf (1,58 MB)
MD5: EB9622A296DFC42B6A0EAC2AE0BD38B0
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Diplomska naloga se osredotoča na analizo odprtokodnih orodij za podatkovno rudarjenje z namenom oceniti njihove funkcionalnosti, zmogljivosti in primernosti za različne naloge. Delo zajema priljubljena orodja, kot so, KNIME, Orange in WEKA, ter analizira njihove lastnosti, uporabniško prijaznost, skalabilnost in podprte algoritme. Cilj raziskave je s primerjavo zagotoviti jasno razumevanje prednosti in omejitev posameznih orodij ter pomagati uporabnikom pri izbiri optimalne rešitve za specifične potrebe podatkovnega rudarjenja. Analiza temelji na merilih, kot so zmogljivost predobdelave podatkov, tehnike modeliranja in vizualizacijske možnosti. Rezultati ponujajo praktične vpoglede za raziskovalce in strokovnjake, ki iščejo ustrezno odprtokodno orodje za podatkovno rudarjenje v okviru svojih projektov.
Keywords:podatkovno rudarjenje, analiza podatkov, orodja, WEKA, KNIME, Orange
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[K. Skenderska]
Year of publishing:2025
Number of pages:1 spletni vir (1 datoteka PDF (IX, 35 str.))
PID:20.500.12556/DKUM-94725 New window
UDC:004.62(043.2)
COBISS.SI-ID:255141891 New window
Publication date in DKUM:30.09.2025
Views:176
Downloads:24
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:27.08.2025

Secondary language

Language:English
Title:Comparative analysis of data mining tools
Abstract:The thesis focuses on the analysis of open-source data mining tools with the aim of assessing their functionalities, performance and suitability for various tasks. The study covers open- source tools such as KNIME, Orange and WEKA, and analyzes their features, user-friendliness, scalability and supported algorithms. The aim of the research is to provide a clear understanding of the advantages and limitations of individual tools through comparison and to help users select the optimal solution for specific data mining tasks. The analysis is based on criteria such as data preprocessing capabilities, modeling techniques and visualization capabilities. The results offer practical insights for researchers and professionals who are looking for a suitable open-source data mining tool for their projects.
Keywords:data mining, data analysis, tools, WEKA, KNIME, Orange


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