ALGORITHM FOR SELECTING A SET OF INFORMATIVE SIGNS BASED ON THE INFORMATION MEASUREMENT CRITERIA OF THE IMPORTANCE OF OBJECTS

Authors

  • Gulomjon Primovych Jo'rayev Doctor of Philosophy (PhD) in Technical Sciences, Kashkadarya Regional Center of Pedagogical Excellence , Uzbekistan
  • Saidkul Khujamurodovich Saparov PhD student , Muhammad al- Khorazmi Tashkent Information in the name technologies University, Uzbekistan
  • Uktamjon Bektashovich Allayarov Assistant Tashkent Medicine Academy Termez branch
  • Dilfuza Elmurodovna Rashidova Assistant Samarkand economy and service Institute, Uzbekistan

Keywords:

information measure, object recognition, similarity coefficient, informative symbols, class object, machine learning, data analysis.

Abstract

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.

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Published

2024-09-17

Issue

2024: 30th Tech-Fest:Germany September

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

ALGORITHM FOR SELECTING A SET OF INFORMATIVE SIGNS BASED ON THE INFORMATION MEASUREMENT CRITERIA OF THE IMPORTANCE OF OBJECTS. (2024). Conferencea , 10-15. https://conferencea.org/index.php/conferences/article/view/3505

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