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Comparing Epsilon Greedy and Thompson Sampling model for Multi-Armed Bandit algorithm on Marketing Dataset Izzatul Umami; Lailia Rahmawati
Journal of Applied Data Sciences Vol 2, No 2: MAY 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i2.28


A/B checking is a regular measure in many marketing procedures for e-Commerce companies. Through well-designed A/B research, advertisers can gain insight about when and how marketing efforts can be maximized and active promotions driven. Whilst many algorithms for the problem are theoretically well developed, empirical confirmation is typically restricted. In practical terms, standard A/B experimentation makes less money relative to more advanced machine learning methods. This paper presents a thorough empirical study of the most popular multi-strategy algorithms. Three important observations can be made from our results. First, simple heuristics such as Epsilon Greedy and Thompson Sampling outperform theoretically sound algorithms in most settings by a significant margin. In this report, the state of A/B testing is addressed, some typical A/B learning algorithms (Multi-Arms Bandits) used to optimize A/B testing are described and comparable. We found that Epsilon Greedy, be an exceptional winner to optimize payouts in this situation.
implementing the Expected Goal (xG) model to predict scores in soccer matches Izzatul Umami; Deden Hardan Gautama; Heliza Rahmania Hatta
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.76


Football is a sport that has the most fans in the world. What makes sebak patterns so popular are their uncertain and unpredictable results. There are many factors that affect the outcome of a football match, including strategy, skill, and even luck. Therefore, guessing the results of a soccer match is an interesting problem. All shots are grouped into sections on the playing field and theoretical goal scores are applied to each area. The factors analyzed are: distance of shot from goal and angle of shot in relation to goal. When calculating xG, it is recommended that the distance and angle of the shot are important. The combination of the two xG factors is better calculated than each variable only. In addition, this xG check has been able to relatively accurately identify the mid-table teams that score and concede goals.