Impact of Data Quality on Training Neural Networks in Text Categorization Problems

The question of the influence of the quality of a dataset for training neural networks for text categorization problems is considered. Methods for improving the quality and "purity" of data are considered. Examples with the final indicators of training are given. Conclusions are made about the influence of methods for improving the quality of data on the final learning outcome.