Prediction of Water Quality Classification of the Kelantan River Basin, Malaysia, Using Machine Learning Techniques

Machine Learning (ML) has been used for a long time and has gained wide attention over the last several years. It can handle a large amount of data and allow non-linear structures by using complex mathematical computations. However, traditional ML models do suffer some problems, such as high bias an...

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Bibliographic Details
Main Authors:	Malek, N.H.A (Author), Nasir, S.A.M (Author), Shaadan, N. (Author), Yaacob, W.F.W (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Adaptive boosting algorithm Biochemical oxygen demand decision tree Decision trees Environmental protection Forecasting gradient boosting Gradient boosting Kelantan Basin Linear regression machine learning Machine learning models Machine learning techniques Malaysia methodology Nearest neighbor search Neural networks Quality classification random forest Random forests river basin River basins spatiotemporal analysis supervised machine learning Supervised machine learning Support vector machines water quality Water quality water quality class Water quality class water quality index Water quality indexes Water resources
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Prediction of Water Quality Classification of the Kelantan River Basin, Malaysia, Using Machine Learning Techniques

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