Peculiarities of methods for determining the class of stars from photographs using neural networks and machine learning

The research topic was chosen in the context of the development of the star classification algorithm using artificial intelligence based on spectral analysis. The aim of the study is to investigate the application of neural networks and machine learning methods for automated data analysis and determination of the class of stars according to their characteristics using media content. The relevance of the study lies in the need to develop effective methods for the automated classification of stars due to the increasing volume of astronomical data. The research methods include the use of various machine learning models, such as Random Forest, K-Nearest Neighbours, Gaussian Naive Bayes, and Support Vector Machine. The results show that the K-Nearest Neighbours and Support Vector Machine models provide the highest accuracy in star classification, confirming their effectiveness in this context.