Abstract
The object of research is forecasting processes in the case of short sets of tabular data. The subject of research is the data augmentation method for images. Achieving the goal occurs primarily from the study of existing machine learning tools and data augmentation methods for images. Further software development to implement various data augmentation methods and machine learning models for images. Approbation of the work was carried out by analyzing the effectiveness of various methods of data augmentation for images using quality metrics and statistical methods. Due to the results of the research, an analysis of the influence of various methods of data augmentation on the effectiveness of classifiers in images was carried out.
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