Finding dependencies in the corporate environment using data mining

• Published in: E3S web of conferences Vol. 431; p. 5032
• Main Authors: Kozlova, Anastasia, Kukartsev, Vladislav, Melnikov, Vladimir, Kovalev, Georgiy, Stashkevich, Alexander
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Les Ulis EDP Sciences 01.01.2023
• Subjects: Artificial neural networks; Correlation analysis; Data mining; Neural networks; Work environment; Working conditions
• ISSN: 2267-1242; 2555-0403; 2267-1242
• DOI: 10.1051/e3sconf/202343105032

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.