An Improved Model for House Price/Land Price Prediction using Deep Learning

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Author(s): Basetty Mallikarjuna (Galgotias University, India), Sethu Ram M. (Sri Padmavati Mahila Visvavidyalayam, India), Supriya Addanke (Sri Padmavati Mahila Visvavidyalayam, India)and Munish Sabharwal (Galgotias University, India)
Copyright: 2022
Pages: 12
Source title: Handbook of Research on Advances in Data Analytics and Complex Communication Networks
Source Author(s)/Editor(s): P. Venkata Krishna (Sri Padmavati Mahila University, India)
DOI: 10.4018/978-1-7998-7685-4.ch005

Keywords: Data Analysis and Statistics / Information Science Reference / Media & Communications / Wireless Systems

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Abstract

House price predictions are a crucial reflection of the economy; sometimes house prices include the land prices and demand of the place and location. The house price and land price are two different things, but both are important for both buyers and sellers. This chapter introduced the combination of ML and DL approaches to predict the house price with the updated regression algorithm. The algorithm named as ‘Mopuri algorithm' reads the 14 attributes like crime rate, population density, rooms, etc. and produces the cost estimation result as a prediction. The proposed model accurately estimates the worth of the house as per the given features. The results of the model tested with the different datasets existing in the Kaggle data source using Python libraries with the Jupyter platform and continuation of the model using the Android OS to develop the smart home web-based application.

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An Improved Model for House Price/Land Price Prediction using Deep Learning

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