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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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書誌詳細
主要な著者:	Momade, Mohammed Hamza, Shahid, Shamsuddin, Hainin, Mohd. Rosli, Nashwan, Mohamed Salem, Umar, Abdulhakim Tahir
フォーマット:	論文
出版事項:	Taylor and Francis Ltd. 2020
主題:	TA Engineering (General). Civil engineering (General)
オンライン･アクセス:	http://eprints.utm.my/id/eprint/90632/ http://dx.doi.org/10.1080/15623599.2020.1744799
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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