2015
DOI: 10.14257/ijseia.2015.9.6.05
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Classification Model for Water Quality using Machine Learning Techniques

Abstract: The problem of water pollution is increasing every day, due to the industries '

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Cited by 50 publications
(27 citation statements)
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“…Summary of the experiment 1 result using 53 attribute We generated 35 classification models with different classifiers and feature selection algorithms [4]. Experiments taken using ConsistencySubsetEval, CfsSubsetEval,…”
Section: Resultsmentioning
confidence: 99%
“…Summary of the experiment 1 result using 53 attribute We generated 35 classification models with different classifiers and feature selection algorithms [4]. Experiments taken using ConsistencySubsetEval, CfsSubsetEval,…”
Section: Resultsmentioning
confidence: 99%
“…Before comparing the proposed model to other classification algorithm and model, it is analyzed the proposed model so that important features can be determined which are presented to classify Kinta River (Perak Malaysia) water quality. Finally, overall observations prove that lazy typesarchetypalenforcing the algorithm of K-star to classify WQ is agreatest algorithm [8].…”
Section: Salisuyusaf Et Al [2015]mentioning
confidence: 86%
“…Most of these articles use different scientific methods, approaches and ML models to predict air quality. S. Y. Muhammed et al in [12] points out that machine learning algorithms are best suited for air quality prediction. Some of them are discussed below.…”
Section: Machine-learning Prediction Modelsmentioning
confidence: 99%