Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions-Reference-Cited by-同舟云学术

Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions

Published:2022-01 Issue: Volume:208 Page:109244
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Otchere Daniel Asante^ORCID,Ganat Tarek Omar Arbi,Ojero Jude Oghenerurie,Tackie-Otoo Bennet Nii,Taki Mohamed Yassir

Funder

Universiti Teknologi Petronas

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference25 articles.

1. Comparative analysis of feature selection-based machine learning techniques in reservoir characterisation;Akande,2015

2. User's guide to correlation coefficients;Akoglu;Turkish J. Emerg. Med.,2018

3. Sigmis: a feature selection algorithm using correlation based method;Blessie;J. Algorithm Comput. Technol.,2012

4. Ensembles for feature selection: a review and future trends;Bolón-Canedo;Inf. Fusion,2019

5. Convex Optimization, Convex Optimization;Boyd,2004

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