Property Valuation Using Linear Regression and Random Forest Algorithm

Sam Goundar, Kunal Maharaj, Anirudh Kumar and Akashdeep Bhardwaj
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Sam Goundar: The University of South Pacific, Suva, Fiji
Kunal Maharaj: The University of the South Pacific, Fiji
Anirudh Kumar: The University of the South Pacific, Fiji
Akashdeep Bhardwaj: University of Petroleum and Energy Studies, Dehradun, India

International Journal of System Dynamics Applications (IJSDA), 2021, vol. 10, issue 4, 1-16

Abstract: The economic boom over the recent past and the quest to further develop has made several nation states the business hubs in their regions. Along with the investments, there has been growth in the number of property sales. Social media has become convenient platform of choice for advertising property sales after the introduction of Web 2.0. This article utilizes social media platforms like Facebook to scrape data from user groups advertising properties and then using data mining techniques and approaches to determine true valuation of properties. This methodology is based on set attributes in the urban areas by looking at the property sales of the recent past within the same area. This enables investors interested in these properties and provides a fair idea of price of properties based on the key attributes associated with the respective property.

Date: 2021
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