Reduced Noise SMOTE in Machine Learning Model: Application in Water Quality Classification with Imbalanced Datasets

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Reduced Noise SMOTE in Machine Learning Model: Application in Water Quality Classification with Imbalanced Datasets

Achieving accurate classification in imbalanced datasets, especially for environmental data such as water quality assessment, is a major challenge for machine learning classifiers. This study introduces the Reduced Noise-Synthetic Minority Oversampling Technique (RN-SMOTE) to address the problems of...

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Bibliographic Details
Published in:	2024 5th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2024 - Proceedings
Main Author:	Nasaruddin N.; Masseran N.; Idris W.M.R.; Ul-Saufie A.Z.
Format:	Conference paper
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209693380&doi=10.1109%2fAiDAS63860.2024.10730391&partnerID=40&md5=2676def56948cc6cbe10c9ca564deb1c

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