Abstract
Most of India's wealth and economy are derived from agriculture. Crop production price forecasting has always been a challenge for farmers. Climatological changes as well as other market variables have resulted in significant losses for farmers. Despite their best efforts, farmers are unable to sell their crops for the prices they want. A decision-assistance model for agricultural product price forecasting is being developed in this project. Farming decisions may be made using this method, which takes into consideration elements like yearly rainfall, WPI, and so on. A year's worth of forecasts are available from the technology. The system employs a machine learning regression approach known as decision tree regression.
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