USING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY

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Date

2019

Journal Title

Journal ISSN

Volume Title

Publisher

СДУ хабаршысы - 2019

Abstract

Abstract. 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.

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Keywords

house price, decision tree, random forest regression model, Almaty, СДУ хабаршысы - 2019, №3

Citation

D. Zhumabek , A. Zhailaubek , A. Temirali , Zh. Rayev / USING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY / СДУ хабаршысы - 2019