Machine Learning Application to Performance for Forecasting Horse Racing
- 주제(키워드) Machine Learning
- 주제(DDC) 658
- 발행기관 아주대학교 일반대학원
- 지도교수 박민재
- 발행년도 2025
- 학위수여년월 2025. 8
- 학위명 석사
- 학과 및 전공 일반대학원 비즈니스애널리틱스학과
- 실제URI http://www.dcollection.net/handler/ajou/000000035274
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
Each country's horse racing industry is seeking a survival strategy in the non-contact environment. In particular, some countries are trying to overcome the current crisis by allowing online ticket sales. In order for online ticket sales to be carried out and activated smoothly, trust-based game management is essential. This study aims to suggest a method that can be applied to the horse racing industry by using data science method and machine leaning techniques. A combination of various variables affecting the horse race is presented and the critical influencing factors are analyzed through the Korean horse racing data over 10 years to investigate the relative importance of the influence of each variable on the race. These attempts highlight the availability and the need for competency in data science technique-based analysis that can bring innovations to the horse racing industry
more목차
1. Introduction 1
2. Literature Reivew 3
2.1 The Characteristics of Horse Racing Industry and Data Analysis 3
2.2 Data Analysis by Machine Learning 7
3. Method 10
3.1 Data 10
3.2 Research Model 12
3.3 Analysis 13
3.3.1 Random Forest Model 13
3.3.2 XGBoost Model 14
3.3.3 CatBoost Model 15
3.4 Results 16
4. Conclusion 17
5. Limitation and Further Study 19
Reference 20
