Methods of combating retraining in neural networks

The presented article is devoted to an urgent issue in the field of the development of artificial neural networks related to retraining. The article analyzes such basic information about the presented problem as relevance, as well as the need and tools for its resolution. As a result of the work, the author provides some of the most common and effective methods aimed at combating retraining in neural networks. The author highlights the principles of operation and the main features of each of the presented methods. In conclusion, the result of the work is presented, as well as trends related to the topic of the presented research are noted. The paper uses theoretical research methods, as well as the results of scientific research of foreign and domestic authorship.