Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions
Feature Selection, a critical data preprocessing step in machine learning, is an effective way in removing irrelevant variables, thus reducing the dimensionality of input features. Removing uninformative or, even worse, misinformative input columns helps train a machine learning model on a more gene...
| Main Authors: | Otchere, D.A., Ganat, T.O.A., Ojero, J.O., Tackie-Otoo, B.N., Taki, M.Y. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.28851 / |
| Published: |
Elsevier B.V.
2022
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113218886&doi=10.1016%2fj.petrol.2021.109244&partnerID=40&md5=82a135f80f4b611a342755fe48872095 http://eprints.utp.edu.my/28851/ |
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