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for solving problems by linear regression using machine learning. A model has been created that predicts

selenocentric system on the basis of coordinates transformation using the regression modeling

namics over the past 10 years. Using the methods of multivariate statistical analysis, a model

while maintaining accuracy. Of the four models, linear regression, Bayesian regression, random forest

where symbolic regression methods have been used for a long time to build models that are both

Approaches to economic and mathematical taxation models in the conditions of the shadow economy

of the reduced regression models allowed to show that the slope angle of the regression curve for male and female

curves was found and linear regression and gradient boosting models were constructed

of the parameters, but also the structure of the models. Examples of ap-plication of one of the symbolic regression

regression model showed the worst. This allowed us to conclude, that in order to minimize classification

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