ALGORITHM FOR CLASSIFYING DOCUMENTS OF A SCIENTIFIC AND EDUCATIONAL ORGANIZATION USING MACHINE LEARNING METHODS

Abstract

Intelligent analysis is used in almost all areas of technology. Machine learning does not stand still and is constantly evolving. Given the transition in modern society to electronic document management, the main assumption in them is that the training and test data must be in the same feature space and follow the same distribution. In real applications, this is not always the case. In this case, the role of transfer learning can be distinguished since transfer learning does not make the same distributional assumptions as traditional machine learning and reduces dependencies on the target task and training data, and has a wider knowledge migration. The article proposes a transfer learning algorithm for document categorization based on clustering. An experiment is also used to test the algorithm. The experiment shows that the algorithm proposed in this article has its advantages.