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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM22407
Volume:
7 |
5 |
May 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
House price forecasting is an important topic of real estate. The literature attempts to derive useful knowledge from historical data of property markets. Machine learning techniques are applied to analyse. Historical property transactions in Bangalore City to discover useful models for house buyers and sellers. Moreover, experiments demonstrate that the Multiple Linear Regression that is based on mean squared error measurement is a competitive approach.The project aims at building a model of housing prices to predict median house value in Bangalore City using the provided dataset this model should learn from the data and be able to predict the median housing price in any district given all the other metrics.
KEYWORDS
Publication Date
5/31/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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