Modelling labour productivity using SVM and RF: a comparative study on classifiers performance
The purpose of this paper is to propose a data-driven approach for preparation of Construction Labour Productivity (CLP) models from influencing labour factors. Two state-of-art machine learning-based classifiers, Support Vector Machine (SVM) and Random Forest (RF) were used for modelling CLP. First...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Taylor and Francis Ltd.
2020
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/90632/ http://dx.doi.org/10.1080/15623599.2020.1744799 |
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