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EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing pp 259–268Cite as

Predicting Property Prices: A Universal Model

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Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

The aim of this chapter is to develop a universal model for predicting property prices. The model can be used for estimating the worth of a property that is not trending. Also the developed model can figure out which components factors the property prices most. This model will also help in knowing the factors which influence the property prices in a particular region.

Property prices are important reflection of economy. Price ranges are of great interest to both buyers and sellers. In this chapter, property prices are predicted based on explanatory factors that cover many aspects of residential properties. The property prices are predicted using Improved Linear Regression model for the specific selected region. To have a generalized universal model, clustering is done on the predicted regional property prices.

Taking into consideration that this model is applicable for any region universally, the accuracy may be compromised for some areas initially. Applying suitable Machine Learning algorithms guarantees improved accuracy with every prediction.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India

    E. Poovammal, Mayank Kumar Nagda & K. Annapoorani

Authors
  1. E. Poovammal
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  2. Mayank Kumar Nagda
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  3. K. Annapoorani
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Corresponding author

Correspondence to E. Poovammal .

Editor information

Editors and Affiliations

  1. Department of Computer Science & Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Anandakumar Haldorai

  2. Department of Computer Science & Engineering, Presidency University, Bengaluru, India

    Arulmurugan Ramu

  3. Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Sudha Mohanram

  4. Department of Electrical Engineering, Faculty of Engineering, University of Malaysia, Kuala Lumpur, Kuala Lumpur, Malaysia

    Chow Chee Onn

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Poovammal, E., Nagda, M.K., Annapoorani, K. (2020). Predicting Property Prices: A Universal Model. In: Haldorai, A., Ramu, A., Mohanram, S., Onn, C. (eds) EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-19562-5_26

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  • DOI: https://doi.org/10.1007/978-3-030-19562-5_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19561-8

  • Online ISBN: 978-3-030-19562-5

  • eBook Packages: EngineeringEngineering (R0)

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