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Original Article
Insurance Cost Prediction Using Polynomial Ridge Regression and Random Forest Classifier
G. Rajeswari1
J.V. Kowsalya2
T.S. Navalakshmi3
N.S Sakthi Aashitha4
T.S Sakthi Jothi5
1Assistant Professor, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India. 2345 Final Year Students, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India.
Published Online: March-April 2025
Pages: 41-43
Cite this article
No DOIReferences
1. A. Ravishankar Rao, Subrata Gardaí, Coumarate Dey, Hang Peng, “Building predictive models of healthcare costs with open healthcare
data”,2020 IEEE International Conference on Healthcare Informatics (ICHI) | 978-1-7281-5382- 7/20/$31.00 ©2020 IEEE | DOI:
10.1109/ICHI48887.2020.9374348
2. Sheng Yao Zhou, Run tong Zhang*, “A Novel Method for Mining Abnormal Expenses in Social Medical Insurance” Auckland University of
Technology. Downloaded on November 07, 2020 at 17:01:50 UTC from IEEE Xplore.
3. Anuja Tike, Sanket Tavarageri,”A Medical Price Prediction System using Hierarchical Decision Trees”,2017 IEEE International Conference
on Big Data (BIGDATA )
4. Pei Shen, “Factor Analysis of Medical Expenses of the Hepatitis A patients in Guangdong”, 2016 8th International Conference on Information
Technology in Medicine and Education.
data”,2020 IEEE International Conference on Healthcare Informatics (ICHI) | 978-1-7281-5382- 7/20/$31.00 ©2020 IEEE | DOI:
10.1109/ICHI48887.2020.9374348
2. Sheng Yao Zhou, Run tong Zhang*, “A Novel Method for Mining Abnormal Expenses in Social Medical Insurance” Auckland University of
Technology. Downloaded on November 07, 2020 at 17:01:50 UTC from IEEE Xplore.
3. Anuja Tike, Sanket Tavarageri,”A Medical Price Prediction System using Hierarchical Decision Trees”,2017 IEEE International Conference
on Big Data (BIGDATA )
4. Pei Shen, “Factor Analysis of Medical Expenses of the Hepatitis A patients in Guangdong”, 2016 8th International Conference on Information
Technology in Medicine and Education.
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