Detecting Water Quality Using KNN, Bayesian and Decision Tree
Xudong Jia · 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML) · 2022
In this study, we have analyzed water quality using different approaches: descriptive analysis and machine learning. First, we get the data source from kaggle website. After processing the data, we use Python sklearn package for data mining. Firstly, the machine learning data mining method is selected through description analysis. Finally, we choose KNN, Bayesian algorithm and decision tree to analyze the water data from kaggle website. The goal is to divide the data into available and unavailable by machine learning algorithm. Finally, through these three methods, we get the results of three methods and make some corresponding comparison and analysis.