Browsing by Author "Zhumabek D."

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    Analysis and the development of a mathematical model of the children mortality
    (Faculty of engineering and natural sciences, 2019) Zhumabek D.
    The mortality rate depends on many different factors: the socio-economic development of the country, the environmental situation. the well-being of the population. the level of stress and much more. After fertility. it takes the second place in its importance in the processes of reproduction of the population. has a serious impact on the population size. its structure. and is closely interconnected with all socio-demographic processes. The causes of mortality in Kazakhstan are classified by the main groups: infectious discases. diseases of the respiratory system. circulatory system, neoplasms. accidents, poisonings and injuries. Mortality of the population is a mirror reflection of the level of socio-economic development of society.
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    MULTIVARIATE REGRESSION ANALYSIS AND MODELLING ON CARS DATASET
    (СДУ хабаршысы - 2019, 2019) Rayev Zh. ; Aipenova A. ; Suleizhan T. ; Zhumabek D. ; Duman A.
    Abstract. The results of the work are based on the construction of a mathematical model for determining unknown parameters using multivariate regression analysis. Structured data are given for the derivation and elimination of significant factors and coefficients. Also, machine learning simple regression models are used for modelling. The results have been evaluated and shown for comparative purposes.
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    USING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY
    (СДУ хабаршысы - 2019, 2019) Zhumabek D. ; Rayev Zh. ; Zhailaubek A. ; Temirali A.
    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.