A Model of Recognition Algorithms Based on Threshold Functions for Assessing Proximity of Objects
Year: 2025
Type: article
Abstract: A model of recognition algorithms for solving the problems of classifying the objects presented in a feature space of large dimensions is constructed. A new approach to developing such a model is proposed based on constructing a set of representative features and determining a suitable set of n/a three-dimensional threshold functions in the process of generating an extreme recognition algorithm. A structural description of the proposed model of recognition algorithms in the form of a sequence of computational procedures is given. Parameterization of these algorithms has been carried out, which makes it possible to set and solve the problem of determining an extreme recognition algorithm within the limits of the created model. The results of a comparative analysis of the proposed and known recognition algorithms are given. Keywords: pattern recognition, model of recognition algorithms, algorithms for calculating estimates, subset of strongly related features, representative feature, three-dimensional threshold function.
Source: Kibernetyka ta Systemnyi Analiz
Language: English
Topic: Machine Learning and ELM
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4406735656