Water Quality Prediction Using Machine Learning

Abstract

This paper shows the use of ML algorithms for the prediction of water quality. The model is trained on Water Quality dataset from Kaggle and it consists of key features such as, pH value, hardness, solids etc. Algorithms used were SVM, Random Forest and Decision Tree. Also, hyperparameter tuning was done in SVM for improving the accuracy using Grid Search technique. The Random Forest algorithm out-performed the others with an accuracy of 68%. Hence, it shows that ML can be used for predicting the quality of water.