Open AccessA study of decision tree application in the problem of accounting for non-insured periods of a pensioner
Author(s) -
L. V. Naykhanova,
A. A. Buldaev,
N. N. Ausheeva,
I. V. Naykhanova,
N. B. Haptahaeva
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1333/3/032055
Subject(s) - decision tree , computer science , tree (set theory) , task (project management) , machine learning , variable (mathematics) , artificial intelligence , legislation , mathematics , engineering , mathematical analysis , systems engineering , law , political science
The article is devoted to the study of machine learning algorithm “decision Tree” for solving the problem “Accounting for non-insured periods”. In pension legislation, there are problems that required a large amount of combinatorial calculations. These include the problem of “Accounting for non-insured periods”. To solve similar problems, machine learning methods should be suitable. To implement the algorithm, training and test samples are created by means of a random number sensor. However, studies have shown that the use of this method gives satisfactory results, but not acceptable for this task. The authors conclude that it is necessary to investigate other, more complex machine learning algorithms, or to find a new dependence of the output variable on the input variables. This dependence is probably to be nonlinear that will determine a choice of a new method of machine learning.