기계학습을 활용한 게임승패 예측 및 변수중요도 산출을 통한 전략방향 도출

Predicting Game Results using Machine Learning and Deriving Strategic Direction from Variable Importance

초록

In this study, models for predicting the final result of League of Legends game were constructed for each rank using data from the first 10 minutes of the game. Variable importance was extracted from the prediction models to derive strategic direction in early phase of the game. As a result, it was possible to predict final results with over 70% accuracy in all ranks. It was found that early game advantage tends to lead to the final win and this tendency appeared stronger as it goes to challenger ranks. Kill(death) was found to be the most influential factor for win, however, there were also variables whose importance rank changed according to rank. This indicates there is a difference in the strategic direction in the early stage of the game depending on the rank.

키워드

Machine LearningClassificationLeague of Legends기계학습분류리그오브레전드
제목
기계학습을 활용한 게임승패 예측 및 변수중요도 산출을 통한 전략방향 도출
제목 (타언어)
Predicting Game Results using Machine Learning and Deriving Strategic Direction from Variable Importance
저자
김용우김영민
DOI
10.7583/JKGS.2021.21.4.3
발행일
2021-08
저널명
한국게임학회 논문지
21
4
페이지
3 ~ 12

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