USING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY

dc.contributor.authorZhumabek D.
dc.contributor.authorRayev Zh.
dc.contributor.authorZhailaubek A.
dc.contributor.authorTemirali A.
dc.date.accessioned2023-11-21T04:42:26Z
dc.date.available2023-11-21T04:42:26Z
dc.date.issued2019
dc.description.abstractAbstract. In real estate valuation and house market research, house prices and rental value are generally analyzed by decision tree regression and random forest regression model based on machine learning. Regression model examines the effect of characteristics of goods on their prices. Factors that determine the house prices in Almaty are analyzed in this paper using real dataset from legal site. The most important variables that affect house rents are type of house, type of building, number of rooms, size, and other structural characteristics such as water system, pool, natural gas. Also used jupyter notebook, numpy, pandas, matplotlib, scipy and scikit-learn.
dc.identifier.citationD. Zhumabek , A. Zhailaubek , A. Temirali , Zh. Rayev / USING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY / СДУ хабаршысы - 2019
dc.identifier.issn2415-8135
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/833
dc.language.isoen
dc.publisherСДУ хабаршысы - 2019
dc.subjecthouse price
dc.subjectdecision tree
dc.subjectrandom forest regression model
dc.subjectAlmaty
dc.subjectСДУ хабаршысы - 2019
dc.subject№3
dc.titleUSING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY
dc.typeArticle

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