(untitled) (Conferencea, 2024)
In this work describes the algorithm developed based on information measurement criteria for evaluating the importance of objects. This algorithm is aimed at selecting informative symbols by determining the degree of similarity of objects. Based on the similarity coefficient and important information indicators, the differences between class objects are analyzed and the data volume is optimized. This approach has been proposed as an effective tool that can be applied in the fields of machine learning and data processing.