COMPARATIVE ANALYSIS OF DECISION TREE AND RANDOM FOREST TECHNIQUE FOR ANALYSIS OF WATER IN MAHARASHTRA

This study presents a data model of Classification based onDecision Tree and Random Forest for considering Maharashtra water quality data from several different places. Data model analysis is done in WEKA software.It deals with ten different samples of water with various parameters like pH, Taste, Turbidity, TDS, Aluminum, Calcium and Iron. In this the comparative analysis is done by applying Decision Tree and Random Forest Technique on the sample. By implementing this evaluation technique of Decision Tree and Random Forest, it can be analyzed that few parameters cannot fit into the model. But the variations of the property values affect the quality or productivity of the water. The parametric value must fall within the permitted range of Indian Guidelines and World Health Organization (WHO) drinking water standards.