Somorjit Laishram
R. Santhosh Kumar
P. Priyadarshani
- Student Department of Artifical Intelligence and Data Science, Sri Manakula Vinayagar Engineering College Madagadipet Puducherry India
- Student Department of Artifical Intelligence and Data Science, Sri Manakula Vinayagar Engineering College, Madagadipet Puducherry India
- Student Department of Artifical Intelligence and Data Science, Sri Manakula Vinayagar Engineering College, Madagadipet Puducherry India
Abstract
In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people’s high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it is crucial to understand the current value of a house. This article aims to forecast the current market value of a Chennai property and develop a model that could assist businesses in predicting home prices and help customers make business decisions. The technique consisted of main steps: data understanding, data cleansing, modelling, data standardization etc. In the process, various aspects are considered, such as the quantity of bedrooms and the accessibility of various utilities. A customer can use this forecast to find more feasible solutions that better fit their needs. To estimate the costs of the various dwellings in question, we have employed the Linear Regression Model.
Keywords: dataset; house price prediction; linear regression; regression analysis; machine learning.
[This article belongs to Journal of Artificial Intelligence Research & Advances(joaira)]
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Journal of Artificial Intelligence Research & Advances
| Volume | 11 |
| Issue | 02 |
| Received | February 29, 2024 |
| Accepted | May 26, 2024 |
| Published | July 10, 2024 |
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