On the training sample size and classification performance: An experimental evaluation in seismic facies classification

Machine learning algorithms (MLAs) perform better when enough high-quality training data is provided. However, a lack of training data is frequent in seismic facies classification and many other supervised learning applications. Data labeling for seismic facies classification is time-consuming and r...

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Bibliographic Details
Main Authors: Babikir, I., Elsaadany, M., Sajid, M., Laudon, C.
Format: Article
Published: Elsevier B.V. 2023
Online Access:http://scholars.utp.edu.my/id/eprint/37516/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159765394&doi=10.1016%2fj.geoen.2023.211809&partnerID=40&md5=bb201dd3f5ec9479db4d5d1224cf93c6
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