research-article

A Random Forest Regression Model Predicting the Winners of Summer Olympic Events

Authors:

Kenji YoshigoeAuthors Info & Claims

BDE '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering

Pages 62 - 69

https://doi.org/10.1145/3404512.3404513

Published: 05 July 2020 Publication History

Abstract

From the past Olympic medal lists, we can find that the number of medals of China has been increasing steadily in recent years while we also observe that some countries always occupy the top positions of the Olympic medal list, such as the United States, Britain and Germany. In this work we take the data of the medal lists from the 18th to 31st Summer Olympic Games as a sample and selects GDP, the population, the size of national team and the home advantage as the characteristic parameters to build a random forest regression model to predict the number of medals. The FP-growth algorithm is used to analyze the association rules of the data. And the winners of some events in the 2020 Tokyo Olympic Games are predicted.

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Cited By

He ZWang Z(2024)Prediction of olympic medal count for USA based on robust time series model and computer implementationThird International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)10.1117/12.3033012(165)Online publication date: 5-Jul-2024
https://doi.org/10.1117/12.3033012

Index Terms

A Random Forest Regression Model Predicting the Winners of Summer Olympic Events
1. Information systems
  1. Information systems applications
    1. Data mining
      1. Association rules
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Machine learning theory
      1. Models of learning

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BDE '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering

May 2020

146 pages

ISBN:9781450377225

DOI:10.1145/3404512

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 05 July 2020

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BDE 2020: 2020 2nd International Conference on Big Data Engineering

May 29 - 31, 2020

Shanghai, China

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Cited By

He ZWang Z(2024)Prediction of olympic medal count for USA based on robust time series model and computer implementationThird International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)10.1117/12.3033012(165)Online publication date: 5-Jul-2024
https://doi.org/10.1117/12.3033012

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