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| Main Authors: | , |
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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.20039598 |
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Table of Contents:
- <p>This repository contains the complete Python implementation for predicting jaggery color categories (Golden, Light Brown, Dark Brown) using machine learning models based on soil, water, and chemical parameters.</p> <p>The code includes data preprocessing, model training (Random Forest and Gradient Boosting), cross-validation (including Leave-One-Location-Out), bootstrap validation, and feature importance analysis.</p> <p>The dataset used in this study is not publicly available due to confidentiality agreements with participating production units and farmers. However, access may be granted for academic and non-commercial purposes through the corresponding author.</p> <p>The code enables full reproducibility of the experimental methodology once dataset access is obtained.</p>