Issue |
E3S Web Conf.
Volume 431, 2023
XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023)
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|
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Article Number | 05032 | |
Number of page(s) | 12 | |
Section | IT and Mathematical Modeling in the Environment | |
DOI | https://doi.org/10.1051/e3sconf/202343105032 | |
Published online | 13 October 2023 |
Finding dependencies in the corporate environment using data mining
1 Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia
2 Bauman Moscow State Technical University, 105005 Moscow, Russia
3 ITMO University, 197101 St. Petersburg, Russia
* Corresponding author: ankoz9@yandex.ru
The article analyses the influence of factors of the work environment, as well as the non-work environment, on the employee's departure from the company. A dataset containing 1470 data rows with 14 attributes belonging to the company's employees was selected for the analysis. The method of self-organising Kohonen maps was used, which allow to study the structure of the data and identify hidden patterns, as well as the method of artificial neural networks, which allow to analyse large amounts of data and find hidden relationships that may not be obvious to humans. In the course of the work, the errors of the methods were determined, several experiments with different number of factors were conducted, and the dependence between the number of factors and the magnitude of the error of the algorithms was revealed. For both methods and each experiment, conjugacy tables were obtained, which contain the classification results obtained by the methods. In addition, a correlation analysis was performed to determine the degree of association between the factors and the target variable.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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