Application of Machine Learning Techniques to Predict the Impact of Health Insurance on the Wellbeing of an Individual
Poornima Taranath1, Sweta Das2, Gowrishankar S.3
1Poornima Taranath*, Department of Computer Science & Engineering, Dr.Ambedkar Institute of Technology, Bengaluru, Karnataka, India.
2Sweta Das, Department of Computer Science & Engineering, Dr.Ambedkar Institute of Technology, Bengaluru, Karnataka, India.
3Gowrishankar S, Department of Computer Science & Engineering, Dr.Ambedkar Institute of Technology, Bengaluru, Karnataka, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 3065-3070 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7247129219/2019©BEIESP | DOI: 10.35940/ijitee.B7247.129219
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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: The healthcare domain in India has suffered considerably despite the advancement in technology. Several financing schemes are endorsed by the insurance companies to lessen the financial burden faced by the government and people. Nonetheless, Health Insurance segment in India remains underdeveloped due to various complexities that it faces. This paper exploits a heuristic sampling approach combined with the ensemble Machine Learning algorithms on the large-scale insurance business data to realize the current shape of the Health Insurance industry in India. Through the courtesy of Data Mining and Data Analytics, it is plausible to furnish insights that assist the common people in acquiring closure that helps in the process of decision making.
Keywords: Data Analysis, Machine Learning, Web Scraping, Health Insurance, Sentimental Analysis.
Scope of the Article: Machine Learning