Quality Assessment of Ground Water in Pre- and Post-Monsoon Using Various Classification Technique
Aiswarya Vijayakumar1, A S Mahesh2 
1Aiswarya Vijayakumar, Department of Computer Science & IT, Amrita School of Arts & Sciences Kochi, Amrita Vishwa Vidyapeetham India
2A S Mahesh, Department of Computer Science & IT, Amrita School of Arts and Sciences Kochi, Amrita Vishwa Vidyapeetham, India.

Manuscript received on 03 March 2019 | Revised Manuscript received on 08 March 2019 | Manuscript published on 30 July 2019 | PP: 5996-6003 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3709078219/19©BEIESP | DOI: 10.35940/ijrte.B3709.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Quality assessment of water is one of the basic points which have pulled in a lot of thought in the progressing years. Diverse kinds of classification system are most convenient for the examination in this field of study. The present examination investigates the quality of ground water in Agastheeswaram which is located in Tamilnadu. Totally 138 water samples was accumulated in the midst of pre-monsoon (PRM) and post-monsoon (PSM) from the year of 2011 to 2012.The water quality (WQ) evaluation was carried out by assessing chemical parameters for both the seasons. This paper explores various classifier models such as DT, KNN and SVM to achieve prediction of groundwater quality. The classification is done based on the WQI of each sample. A near investigation of characterization systems was done dependent on the confusion matrix, accuracy, f1 score, precision and recall. The outcomes propose that SVM is a better method having high accuracy rate than other models.
Index Terms: Classification Algorithms, Water Quality Index, Support Vector Machine, Decision Tree; K Nearest Neighbors.

Scope of the Article: Classification