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House Price Forecasting using Data Mining

by Nihar Bhagat, Ankit Mohokar, Shreyash Mane
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 152 - Number 2
Year of Publication: 2016
Authors: Nihar Bhagat, Ankit Mohokar, Shreyash Mane
10.5120/ijca2016911775

Nihar Bhagat, Ankit Mohokar, Shreyash Mane . House Price Forecasting using Data Mining. International Journal of Computer Applications. 152, 2 ( Oct 2016), 23-26. DOI=10.5120/ijca2016911775

@article{ 10.5120/ijca2016911775,
author = { Nihar Bhagat, Ankit Mohokar, Shreyash Mane },
title = { House Price Forecasting using Data Mining },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 152 },
number = { 2 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 23-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume152/number2/26292-2016911775/ },
doi = { 10.5120/ijca2016911775 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:57:04.933353+05:30
%A Nihar Bhagat
%A Ankit Mohokar
%A Shreyash Mane
%T House Price Forecasting using Data Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 152
%N 2
%P 23-26
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

People looking to buy a new home tend to be more conservative with their budgets and market strategies. The existing system involves calculation of house prices without the necessary prediction about future market trends and price increase. The goal of the paper is to predict the efficient house pricing for real estate customers with respect to their budgets and priorities. By analyzing previous market trends and price ranges, and also upcoming developments future prices will be predicted. The functioning of this paper involves a website which accepts customer’s specifications and then combines the application of multiple linear regression algorithm of data mining. This application will help customers to invest in an estate without approaching an agent. It also decreases the risk involved in the transaction.

References
  1. Vishal Raman, May 2014. Identifying Customer Interest inReal Estate Using Data Mining.
  2. http://www.99acres.com/property-rates-and-price-trendsin-mumbai
  3. Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining, 2015. Introduction to Linear Regression Analysis
  4. Gongzhu Hu, Jinping Wang, and Wenying FengMultivariate Regression Modeling for Home ValueEstimates with Evaluation using Maximum Information Coefficient
  5. Iain Pardoe, 2008, Modeling Home Prices Using Realtor Data
  6. Aaron Ng, 2015, Machine Learning for a London Housing Price Prediction Mobile Application
Index Terms

Computer Science
Information Sciences

Keywords

Data mining house price forecasting prediction linear regression real estate.

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