Analysing Ground Water Quality in the Regions of Kadapa District Using Supervised Learning Methods

Abstract

Traditional Water data analysis methods has a lot of manual work and interpretation of data which is also slow and costly. Data mining technique is used to extract the hidden patterns from the data. Water samples were collected from various regions of Kadapa (District), Andhra Pradesh (State), India. These samples were tested in the laboratory for physico chemical property analysis. Water Quality Index (WQI) were calculated. The goal is to predict the water quality category (whether it is Excellent, Good or poor for drinking purpose) for given test sample(s). Supervised Learning methods and its results were explained to predict the water sample(s). Random forest method provides high accuracy compared to other classification methods.