Leveraging Machine Learning for Accurate Groundnut Price Forecasting in Tamil Nadu: An XGboost Approach
Chow Suliyaa Mantaw,
Prahadeeswaran M
Abstract:Accurate forecasting of agricultural commodity prices is vital for enabling effective decision-making within the agricultural ecosystem. This study addresses the implementation of modern machine learning algorithms, including XGBoost, Automated Machine Learning (AutoML) utilising PyCaret, and Auto-ARIMA, for forecasting groundnut prices in Tamil Nadu. The research integrates key temporal information, such as day of the week, month, and lagged data, to boost the prediction performance. The findings illustrate t… Show more
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