The article considers a solution to a two-class recognition problem using metric al gorithms based on k-nearest neighbors. The proposed solution options are: the classical KNN algorithm based on a nonparametric estimate of the probability density function; the Nadaraya-Watson NW method for calculating the regression dependence based on the determined values of the target feature; calculating estimates in the local neighbor hood of objects and dividing their values into non-overlapping intervals with dominance of representatives of one of the two classes. The optimality criteria were the majority rule for KNN, the accuracy of dividing the values of the target feature on the numerical axis for NW and the stability of object estimates within the interval boundaries. When searching for the optimal k values for the listed options, the sliding control method was used. The results of the obtained solutions are demonstrated on the GERMAN sample from the repository based on the descriptions of 1000 objects in a heterogeneous feature space. The efficiency of choosing the k values based on the stability of object estim.
| Mualliflar | Ignatev , N.A., Tursunmurotov, D.Kh., Игнатьев , Н.А., Турсунмуротов, Д.Х. |
|---|---|
| Jurnal | Ҳисоблаш ва амалий математика муаммолари |
| Nashriyot | Тошкент ахборот технологиялари университети қошидаги, Ахборот-коммуникация технологиялари илмий-инновацион, маркази |
| ISSN | 2181-8460, 2181-046X |
| Nashr sanasi | 2024-10-11 |
| Son | 4 |
| Betlar | 117-125 |
| Til | Ingliz |
| Ilmiy soha | Texnika |
| Indeksga qo‘shilgan | 2026-08-27 |
Nadaraya-Watson method, decision rule, objective function, feature stability, Метод Надарая– Ватсона, решающее правило, целевая функция, устойчивость признака
| APA | Ignatev , N.A., Tursunmurotov, D.Kh., Игнатьев , Н.А., & Турсунмуротов, Д.Х. (2024). On the efficiency of metric recognition algorithms based on k nearest neighbor. Ҳисоблаш ва амалий математика муаммолари, (4), 117-125. https://journals.airi.uz/index.php/pvpm/article/view/36 |
|---|---|
| GOST (OAK) | Ignatev , N.A. va b. On the efficiency of metric recognition algorithms based on k nearest neighbor // Ҳисоблаш ва амалий математика муаммолари. – 2024. – № 4. – P. 117-125. |
| MLA | Ignatev , N.A., Tursunmurotov, D.Kh., Игнатьев , Н.А., and Турсунмуротов, Д.Х. “On the efficiency of metric recognition algorithms based on k nearest neighbor.” Ҳисоблаш ва амалий математика муаммолари, (4), 117-125, 2024. https://journals.airi.uz/index.php/pvpm/article/view/36 |
| Chicago | Ignatev , N.A., Tursunmurotov, D.Kh., Игнатьев , Н.А., and Турсунмуротов, Д.Х. “On the efficiency of metric recognition algorithms based on k nearest neighbor.” Ҳисоблаш ва амалий математика муаммолари, (4), 117-125 (2024). https://journals.airi.uz/index.php/pvpm/article/view/36 |
| Harvard | Ignatev , N.A., Tursunmurotov, D.Kh., Игнатьев , Н.А., and Турсунмуротов, Д.Х (2024) ‘On the efficiency of metric recognition algorithms based on k nearest neighbor’, Ҳисоблаш ва амалий математика муаммолари, (4), 117-125. https://journals.airi.uz/index.php/pvpm/article/view/36 |
| BibTeX | @article{ignatevna2024,
title = {On the efficiency of metric recognition algorithms based on k nearest neighbor},
author = {Ignatev , N.A. and Tursunmurotov, D.Kh. and Игнатьев , Н.А. and Турсунмуротов, Д.Х.},
journal = {Ҳисоблаш ва амалий математика муаммолари},
year = {2024},
number = {4},
pages = {117-125},
url = {https://journals.airi.uz/index.php/pvpm/article/view/36}
} |
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