This research paper proposes a methodology for processing datasets based on modern methods. Iterative imputation based on decision trees was used to systematically replace missing values in the dataset. The remaining irregular part of the missing values was filled in using the SVD imputation method based on Matrix Factorization. The data's extreme values and outliers were stabilized using a logarithmic transformation. The prepared data was trained on decision trees and ensemble models based on them. The effectiveness of the proposed ensemble approaches in classifying crop types based on soil data was evaluated on training, validation, and test sets, and the results were analyzed.
| Mualliflar | A. Akhatov, F. Nazarov |
|---|---|
| Jurnal | Samarqand davlat universiteti ilmiy tadqiqotlar axborotnomasi |
| Nashr sanasi | 2026-01-01 |
| Jild | 1 |
| Son | 1 |
| Betlar | 65-74 |
| DOI | 10.59251/2181-3973.2025.v1.138.1.3759 |
DOI: 10.59251/2181-3973.2025.v1.138.1.3759 · Maqolaning asl sahifasi
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