Podatkovno rudarjenje pri iskanju najkoristnejšega posameznika košarkarske lige nba

diplomsko delo

Jaša Kšela (Author), Iztok Fister (Mentor)

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;šport;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2020
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[J. Kšela]
UDC:	004.65:796.323.2(043.2)
COBISS:	38013443
Views:	409
Downloads:	46
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	The use of data mining as an aid for finding the most valuable player in nba
Secondary 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.
Secondary keywords:	data mining;basketball;machine learning;NBA;sport;
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages:	VIII, 32 f.
ID:	11949245