Application of Data Mining Techniques to Examine Quality of Water
R.Subhashini1, J.K.Jeevitha2, B. Keerthi Samhitha3
1R.Subhashini, Professor, School of Computing, Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.
2J. K. Jeevitha, Assistant Professor, Department of Information Technology, PSNA College of Engineering and Technology, Dindigul.
3B. Keerthi Samhitha, Assistant Professor, School of Computing, Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.
Manuscript received on 05 March 2019 | Revised Manuscript received on 17 March 2019 | Manuscript Published on 22 March 2019 | PP: 613-617 | Volume-8 Issue-5S April 2019 | Retrieval Number: ES3493018319/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Water is one of the most used natural resources. Increase in content of harmful chemicals is one of the main reasons which will affect quality of water. Continuous monitoring and early forecasting can help us in maintaining quality of water. Data mining is one of the most efficient techniques that can effectively perform this operation. It is the process to discover interesting information from even large amounts of data. In this paper we are going to make use of R tool to perform data mining for water samples.
Keywords: Multiple linear Regression; Randomforest; Regression Tree; Model Evaluation;
Scope of the Article: Security Technology and Information Assurance