Using extreme gradient boosting (XGBoost) machine learning to predict construction cost overruns
Author:
Affiliation:
1. Department of Building Technology, Ho Technical University, Ho, Volta Region, Ghana
2. Wits Business School, University of the Witwatersrand, Johannesburg, South Africa
Publisher
Informa UK Limited
Subject
Management of Technology and Innovation,Strategy and Management,Building and Construction,Architecture
Link
https://www.tandfonline.com/doi/pdf/10.1080/15623599.2023.2289754
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3. Risk perception and Bayesian analysis of international construction contract risks: The case of payment delays in a developing economy
4. Ahiaga-Dagbui DD Smith SD. 2012. Neural networks for modelling the final target cost of water projects.
5. Systematic literature review of project manager's leadership competencies
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