Abstract

The relevance of the article lies in the description of the process of data analysis and modeling for solving the placement problem. The main purpose of the research work is to solve the problem of location and assess the degree of influence of the geographical characteristics of locations on the indicators of the economic efficiency of the organization. The article defines the concepts of economic efficiency and profit, as well as how they are related to each other. A number of tasks are described in solving the placement problem. Questions regarding the geographic data used and the formation of the target variable are covered in detail, namely, the questions are answered. What? How? Why? What-what factors can be used to identify the potential of a location. How is the processing of data on store revenues to the final form of the target variable, why such transformations are needed. The process of correlation analysis and feature selection for the subsequent stage of modeling is shown. The course of building the model and assessing its accuracy is described. And also the analysis of the residuals for the best combinations was carried out using the methods of non-parametric statistics. The main tools in the process of solving these problems were the Python programming language and its libraries pandas, numpy, scikit-learn, xgboost, hyperopt, statsmodels, scipy, matplotlib, seaborn. The result of this research work is the constructed machine learning models to determine the economic potential of a location.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.