CLUSTERING AND CLASSIFICATION OF UZBEKISTAN'S REGIONS BY AGRICULTURAL INDICATORS USING A MACHINE LEARNING APPROACH

Ismailov , Ilkhom, Rakhimov , Rustamjon

Techscience.uz - техника фанлари долзарб масалалри · 2026-yil

Annotatsiya

In this article, the agricultural indicators of 12 regions of the Republic of Uzbekistan and the Republic of Karakalpakstan for the years 2010–2024 were analyzed using machine learning, and the regions — including the Republic of Karakalpakstan — were divided into clusters based on their performance efficiency. The database was obtained from the official website of the National Statistics Committee of the Republic of Uzbekistan at https://stat.uz. A total of 36 agricultural indicators were collected and used for analysis. The K-Means and Hierarchical Clustering machine learning algorithms were applied. Based on the agricultural data, the regions and the Republic of Karakalpakstan were divided into 3 clusters using K-Means and Hierarchical Clustering algorithms

Maqola ma’lumotlari
MualliflarIsmailov , Ilkhom, Rakhimov , Rustamjon
JurnalTechscience.uz - техника фанлари долзарб масалалри
Nashr sanasi2026-03-25
Jild4
Son3
Betlar92-100
TilIngliz
DOI10.47390/ts-v4i3y2026n12

Kalit so‘zlar

K-Means, Hierarchical Clustering, clustering, agriculture, Machine Learning, Uzbekistan., K-Means, Ierarxik Klasterlash, klasterlash, qishloq xo‘jaligi, Machine Learning, O‘zbekiston.

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