International Conference on Communication, Devices and Computing
ICCDC 2023: Proceedings of the 4th International Conference on Communication, Devices and Computing pp 95–111 Cite as
Real Estate Price Prediction Using Machine Learning
- Shilpa Yadav 41 ,
- Namrata Dhanda 41 ,
- Archana Sahai 42 ,
- Rajat Verma 43 &
- Sakshi Pandey 41
- Conference paper
- First Online: 28 July 2023
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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1046))
Real estate is a type of property that includes both land and structures as well as access to water, minerals, and other natural resources. The following paper provides an example of how a price forecasting implementation for the housing market and real estate market was carried out. There are numerous algorithms available for price prediction. Real estate price is important to both buyers and sellers. The usual methods of the quantifying price of real estate are cumbersome. Today, machine learning models are important tools to replace human work with models that can predict the price of real estate. This paper examines which characteristics of real estate property determine the price and provides insight into each of these characteristics. It is well known that many economic parameters can affect property price developments to a greater or lesser extent. In addition, it will be interesting for bankers and investors to know the future development of real estate prices. A key indicator of the economy is the price of real estate. In this study, some ML algorithms like linear regression have been used to predict the cost of a house from given attributes in the housing information set downloaded from Kaggle for Bangalore. The dataset has information about the location of the house, cost, square feet, etc. To reduce the risk of bias, hyperparameters were chosen optimally and the data set was cleaned up before being divided using k-fold cross-validation. Explanatory variables will be used to predict the price that covers many aspects of real estate. The objective of the study is to build a model that can predict the price given the features.
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Department of Computer Science and Engineering, Amity University, Lucknow, Uttar Pradesh, India
Shilpa Yadav, Namrata Dhanda & Sakshi Pandey
Amity Institute of Information Technology, Amity University, Lucknow, Uttar Pradesh, India
Archana Sahai
Department of Computer Science and Engineering, Pranveer Singh Institute of Technology, Kanpur, India
Rajat Verma
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Department of Applied science, Aluminum Research Center REGAL, University of Quebec at Chicoutimi, Chicoutimi, QC, Canada
Dilip Kumar Sarkar
Indian Institute of Technology (ISM), Dhanbad, Jharkhand, India
Pradip Kumar Sadhu
Department of Electronics and Communication Engineering, Central Institute of Technology, Kokrajhar, Assam, India
Sunandan Bhunia
Department of Electronics and Communication Engineering, Haldia Institute of Technology, Haldia, West Bengal, India
Jagannath Samanta
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Yadav, S., Dhanda, N., Sahai, A., Verma, R., Pandey, S. (2023). Real Estate Price Prediction Using Machine Learning. In: Sarkar, D.K., Sadhu, P.K., Bhunia, S., Samanta, J., Paul, S. (eds) Proceedings of the 4th International Conference on Communication, Devices and Computing. ICCDC 2023. Lecture Notes in Electrical Engineering, vol 1046. Springer, Singapore. https://doi.org/10.1007/978-981-99-2710-4_9
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Published : 28 July 2023
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