Classification Based On Decision Trees And Neural Networks
Nilufar NiyozmatovaResearch institute for development of digital technologies and artificial intelligence, Tashkent, Republic of UzbekistanNarzillo MamatovResearch institute for development of digital technologies and artificial intelligence, Tashkent, Republic of UzbekistanBahrixon Ibragimovna OtaxonovaTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Republic of UzbekistanAbdurashid SamijonovTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Republic of UzbekistanKeulimjay ErejepovTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Republic of Uzbekistan
2021 International Conference on Information Science and Communications Technologies (ICISCT)conference2021en
ABI
Annotatsiya
The article is devoted to the approach of classification of texts by decision trees and neural networks, in which the quantitative properties of texts are formed as a set. A detailed description of the approaches and examples of text classification are given. Each approach is compared with classification performance, number of authors, characteristics, and parameters chosen.
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