Machine learning based approach for metaphoric investigation of ground water quality.

Earth is often referred to as the "Blue Planet" because of much of its area covered by water (almost 71%). After air, water plays a fundamental role in human life. On Earth water is there on many different places and in many different forms. Compared to the availability of water for human consumption is limited to that of the amount of water exists. The majority of fresh water is actually found underground as soil moisture and in aquafiers. As population is growing at unprecedented rates globally, protecting groundwater is highest priority. Protecting groundwater directly protects surface water, rain water and all forms of water because water continues to cycle and recycle. For this the immediate action we can take right now is to improve water quality monitoring. Water quality describes the chemical, physical and biological characteristics, usually with respect to its suitability for a particular purpose. Water quality is classified into four main types: Potable Water, Palatable Water, Contam-inated Water and Infected Water. Traditional methods of water quality classification are cumbersome process and hence Machine Learning (ML) can be used as a catalyst for this. This study predicts ground water quality using ML techniques. Hence, the study is mainly useful for prediction of drinkable water. [ABSTRACT FROM AUTHOR]