Application of bayesian network on the example of training model «Rabota»

МРНТИ 28.29.15                                                                                №2 (2020г.)

 

Mamyrbayev O.Zh., Litvinenko N.G., Shayakhmetova A.S., Sultangazieva A.N., Turdalyuly M.   

 

In a modern information environment, the application of artificial intelligence, including the Bayesian approach, is relevant for solving various applied problems. The Bayesian approach is used as a method of adapting existing probabilities to newly obtained experimental data. The main idea of building a Bayesian network is to decompose a complex system into simple elements. The article is devoted to the application of the Bayesian network on the example of the training model “Rabota”. The advantages of Bayesian networks and a real example of use in determining the ability of an applicant to take a vacant position have been considered. The proposed research method takes into account the main factors affecting the assessment of the candidate’s potential for a particular position using the Bayesian approach. The results of the study including probabilistic relationships between individual nodes of the constructed Bayesian network have been presented.
Key words: artificial intelligence, Bayesian networks, probability dependence.

 

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