Algoritmi gručenja v okolju jamovi in programskem jeziku r

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Title:	Algoritmi gručenja v okolju jamovi in programskem jeziku r
Authors:	ID Šuster, Tine (Author) ID Karakatič, Sašo (Mentor) More about this mentor...
Files:	UN_Suster_Tine_2022.pdf (1,47 MB) MD5: EAF4D418927733961E9C4BB57CCD52E3
Language:	Slovenian
Work type:	Bachelor thesis/paper (mb11)
Typology:	2.11 - Undergraduate Thesis
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	Gručenje je uporabna tehnika strojnega učenja. Velika količina podatkov, ki so na voljo odpira mnogo možnosti za iskanje skritega znanja. Ti pogoji ponujajo priložnost razvoja odprtokodnih orodij za uporabo strojnega učenja in ga tako približati več uporabnikom. Opisali smo osnove strojnega učenja in podrobneje analizirali nekaj algoritmov gručenja. V programskem jeziku R smo razvili vtičnik za odprtokodno okolje Jamovi. Končni izdelek podpira tri pogosto uporabljane algoritme gručenja in omogoča uporabniko enostavno gručenje nad podatki prav tako pa oceno pridobljenih rezultatov. Uporabniško izkušnjo smo izboljšali tudi z grafičnim prikazom podatkov.
Keywords:	gručenje, analiza, strojno učenje, vtičnik
Year of publishing:	2022
Source:	Maribor
PID:	20.500.12556/DKUM-82989
Publication date in DKUM:	13.01.2023
Views:	145
Downloads:	23
Metadata:
Categories:	KTFMB - FERI
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License:	CC BY 4.0, Creative Commons Attribution 4.0 International

Link:	http://creativecommons.org/licenses/by/4.0/
Description:	This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:	12.09.2022

Language:	English
Title:	Clustering algorithms in the jamovi environment and the r programming language
Abstract:	Clustering is a useful machine learning technique. The large amount of data available opens up many possibilities for finding hidden knowledge. These conditions offer the possibility of developing open source tools for using machine learning and thus bringing it closer to more users. We described the basics of machine learning and analyzed some clustering algorithms in more detail. In the programming language R, we developed a plug-in for the Jamovi open source environment. The final product supports three commonly used clustering algorithms and allows the user to easily analyze the data, aswell as enabling the assessment of the obtained results. We also improved the user experience with graphical display of the data.
Keywords:	clustering, analysis, machine learning, plugin

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