House Price Prediction Modeling Using Machine Learning

Автор: M. Thamarai, S. P. Malarvizhi

Журнал: International Journal of Information Engineering and Electronic Business @ijieeb

Статья в выпуске: 2 vol.12, 2020 года.

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Machine Learning is seeing its growth more rapidly in this decade. Many applications and algorithms evolve in Machine Learning day to day. One such application found in journals is house price prediction. House prices are increasing every year which has necessitated the modeling of house price prediction. These models constructed, help the customers to purchase a house suitable for their need. Proposed work makes use of the attributes or features of the houses such as number of bedrooms available in the house, age of the house, travelling facility from the location, school facility available nearby the houses and Shopping malls available nearby the house location. House availability based on desired features of the house and house price prediction are modeled in the proposed work and the model is constructed for a small town in West Godavari district of Andhrapradesh. The work involves decision tree classification, decision tree regression and multiple linear regression and is implemented using Scikit-Learn Machine Learning Tool.

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Decision tree, house price prediction, decision tree regression, multiple linear regression

Короткий адрес: https://sciup.org/15017396

IDR: 15017396   |   DOI: 10.5815/ijieeb.2020.02.03

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