House Price Prediction System

Authors

  • Mayur Doke  Department Computer Engineering, Dr. D. Y. Patil School of Engineering, Lohegaon, Pune, Maharashtra, India
  • Rohit Ganguli  Department Computer Engineering, Dr. D. Y. Patil School of Engineering, Lohegaon, Pune, Maharashtra, India

Keywords:

House price prediction, Regression algorithm, Machine learning, Feature extraction.

Abstract

The housing sector has hike as it is the one of the basic need. Housing the main domain of real estate. In the major metropolitan cities and the cities with many prestigious Educational institutions and IT Parks have reasonable price increase in housing. Home buying plans can derails the family’s financial planning and other goals. Now a day’s house price changing rapidly according to various parameters. The buyer gets confused in choosing his dream home as difference in price making it challenging. Both the buyer and seller should satisfy so they do not overestimate or underestimate price. So to build the platform where buyer can find home according to its needs and friendly to its financial condition. House price prediction on different parameters is our goal. Doing that we are going to use regression algorithms using machine learning on dataset so it can extract features from dataset. Result of this approach provide maximum efficiency and minimum errors.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-06-30

Issue

Volume 8, Issue 3, May-June-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Mayur Doke, Rohit Ganguli, " House Price Prediction System" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 3, pp.266-271, May-June-2021.