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Published in:
2023 | OriginalPaper | Chapter
House Pricing Prediction Based on Composite Facility Score Using Machine Learning Algorithms
Authors : Santosh Kumar, Mohammad Haider Syed
Published in: Proceedings of Third International Conference on Computing, Communications, and Cyber-Security
Publisher: Springer Nature Singapore
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Abstract
Various features of a house play some role to determine its price. Out of these, location is the dominant feature to determine the price. Besides location, there are some other features which affect the price of a house like area, sports facility, hospital, 24 × 7 security, etc. In this paper, 40 features, available in dataset of houses, are taken from Kaggle platform and have been considered for prediction of house prices. The data of six different cities of India has been included, and these are Delhi, Bangalore, Hyderabad, Kolkata, Mumbai, and Chennai. Here, we endeavored to develop a predictive model for anticipating the price dependent on a specific number of highlights that influence the price. Six machine learning algorithms are used to develop models and compared based on their accuracy of prediction, and the most accurate model is used to determine the price of houses.