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Title:
Podatkovno rudarjenje pri iskanju najkoristnejšega posameznika košarkarske lige nba : diplomsko delo
Authors:
ID
Kšela, Jaša
(
Author
)
ID
Fister, Iztok
(
Mentor
)
More about this mentor...
Files:
UN_Ksela_Jasa_2020.pdf
(993,75 KB)
MD5: E48B6866775E86C9EF074B1E4D75E57E
PID:
20.500.12556/dkum/c936710f-1291-4cac-b3e1-89c9fb6ae1b9
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Diplomsko delo prikazuje uporabo različnih metod podatkovnega rudarjenja, kot pomoč pri iskanju najkoristnejšega igralca ameriške profesionalne košarkarske lige NBA. Podatkovna baza je bila ustvarjena s pomočjo spletnega luščenja. Izluščene podatke smo nato vizualno predstavili in s pomočjo izvedenih metod strojnega učenja nad njimi poizkušali napovedati prihodnjega najkoristnejšega posameznika. Metode smo na koncu med seboj primerjali.
Keywords:
podatkovno rudarjenje
,
košarka
,
strojno učenje
,
NBA
,
šport
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[J. Kšela]
Year of publishing:
2020
Number of pages:
VIII, 32 f.
PID:
20.500.12556/DKUM-77039
UDC:
004.65:796.323.2(043.2)
COBISS.SI-ID:
38013443
NUK URN:
URN:SI:UM:DK:LR2UYH65
Publication date in DKUM:
03.11.2020
Views:
1134
Downloads:
92
Metadata:
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:
12.08.2020
Secondary language
Language:
English
Title:
The use of data mining as an aid for finding the most valuable player in nba
Abstract:
The diploma thesis describes the usage of different methods of the data mining as an aid for finding the most valuable player in American professional basketball league known as the NBA. Web scraper was used to create database. Scraped data were visualized, and we tried to predict the most valuable player with different methods of machine learning. At the end we compare all of the used methods with each other.
Keywords:
data mining
,
basketball
,
machine learning
,
NBA
,
sport
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