Based on Decision Tree and Improved PCA Algorithm for the Analysis of the Olympic Games in the Future

DOI

10.2991/978-94-6463-230-9_124How to use a DOI?

Keywords

Decision tree; Principal component analysis; Olympic Games; ID3 algorithm; Machine learning

Abstract

In recent years, the Olympic Games have been faced with no country or city to host the situation, mainly because of its events, the number of participants and the scale of investment and other aspects of the host country’s ability to be very high. In this paper, 68 indexes of 211 countries in the world such as economy, infrastructure, international reputation and national quality are collected. After dimensionality reduction of indexes by improved principal component analysis method, eight effective principal components are obtained. Then, based on the eight principal components, the decision tree model and ID3 algorithm are used to evaluate the ability of 211 countries to host the Olympic Games, so as to provide solutions for the future Olympic Games.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yuanhao Zhang
AU  - Jiayi Zhang
PY  - 2023
DA  - 2023/09/04
TI  - Based on Decision Tree and Improved PCA Algorithm for the Analysis of the Olympic Games in the Future
BT  - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
PB  - Atlantis Press
SP  - 1028
EP  - 1036
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-230-9_124
DO  - 10.2991/978-94-6463-230-9_124
ID  - Zhang2023
ER  -