Machine learning for water quality classification

Abstract In the past years, there has been a lot of interest in water quality and its prediction as are many pollutants that affect quality. The techniques provided herein will help us controlling reducing risks pollution. this study, we discuss concepts related to machine learning models their applications for classification (WQC). Three algorithms, J48, Naïve Bayes, multi-layer perceptron (MLP), were used WQC prediction. dataset contains 10 features, order evaluate machine's algorithms performance, some accuracy measurements used. Our study showed proposed can accurately classify By analyzing results, it was found MLP algorithm achieved highest compared other algorithms.