Title:	Relevant Independent Variables on MOBA Video Games to Train Machine Learning Algorithms
Authors:	López-Guzmán, Juan Guillermo Bustacara-Medina, Cesar Julio
Citation:	WSCG 2021: full papers proceedings: 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 171-180.
Issue Date:	2021
Publisher:	Václav Skala - UNION Agency
Document type:	konferenční příspěvek conferenceObject
URI:	http://hdl.handle.net/11025/45022
ISBN:	978-80-86943-34-3
ISSN:	2464-4617 2464–4625(CD/DVD)
Keywords:	rozpoznávání vzorů;systémy doporučení;strojové učení;MOBA;League of Legends;Multiplayer Online Battle Arena
Keywords in different language:	recommender systems;machine learning;MOBA;League of Legends;Multiplayer Online Battle Arena;pattern recognition
Abstract in different language:	Popularity of MultiplayerOnlineBattle Arena (MOBA)video gameshas grown considerably, its popularity as well as the complexity of their playability, have attracted the attention in recent years of researchers from various areas of knowledge and in particular how they have resorted to different machine learning techniques. The papers reviewed mainly look for patterns in multidimensional data sets. Furthermore, these previous researches do not present a way to select the independent variables(predictors)to train the models. For this reason, this paper proposes a listof variables based on the techniques used and the objectives of the research. It allows to provide a set of variables to find patterns applied in MOBA videogames.In order to get the mentioned list,the consulted workswere groupedbythe used machine learning techniques, ranging from rule-based systems to complex neural network architectures. Also, a grouping technique is applied based on the objective of each research proposed.
Rights:	© Václav Skala - UNION Agency
Appears in Collections:	WSCG 2021: Full Papers Proceedings

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.