Implementation of DBSCAN Clustering to Relate Various Parameters to Predict Primary Education Growth Based on Previous Data
Mayank Mittal1, Nitin Goyal2, Mohit Kumar3
1Mayank Mittal, Assistant Professor, Department of CSE, DVSIET, Meerut (Uttar Pradesh), India.
2Nitin Goyal, Assistant Professor, Department of CSE, DVSIET, Meerut (Uttar Pradesh), India.
3Mohit Kumar, Assistant Professor, Department of CSE, DVSIET, Meerut (Uttar Pradesh), India.
Manuscript received on 15 August 2019 | Revised Manuscript received on 27 August 2019 | Manuscript Published on 06 September 2019 | PP: 22-26 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F10050886S19/19©BEIESP | DOI: 10.35940/ijeat.F1005.0886S19
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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: Primary Education can be defined as first step of compulsory education which contributes in the development of future of country. Our aimis to develop a prototype based on DBSCAN Clustering Algorithm to monitor the primary education and corresponding utilization of previous data to estimate and predict the future growth of primary Education in India.The major goal of primary education is achieving basic literacy and numeracy amongst all people as well as establishing foundations in science, mathematics, geography, history & social sciences. DBSCAN Clustering Algorithm can be utilized to establish relationship between human resources, infrastructure, government expenditure, actual utilization of these resources and the outcome which is socio-economic makeover of Society of India. It would help to predict and formulate correct path to transform the process of growth of Indian Primary Education System.
Keywords: Data Education Clustering System.
Scope of the Article: Data Mining