An innovative approach of determining the sample data size for machine learning models: a case study on health and safety management for infrastructure workers-Reference-Cited by-同舟云学术

An innovative approach of determining the sample data size for machine learning models: a case study on health and safety management for infrastructure workers

Published:2022 Issue:9 Volume:30 Page:3452-3462
ISSN:2688-1594
Container-title:Electronic Research Archive
language:
Short-container-title:era

Author:

Wang Haoqing¹,Yi Wen²,Liu Yannick¹

Affiliation:

1. Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

2. Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Abstract

<abstract> <p>Numerical experiment is an essential part of academic studies in the field of transportation management. Using the appropriate sample size to conduct experiments can save both the data collecting cost and computing time. However, few studies have paid attention to determining the sample size. In this research, we use four typical regression models in machine learning and a dataset from transport infrastructure workers to explore the appropriate sample size. By observing 12 learning curves, we conclude that a sample size of 250 can balance model performance with the cost of data collection. Our study can provide a reference when deciding on the sample size to collect in advance.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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