Abstract
Abstract: "India's heavy reliance on agriculture underscores the importance of accurately estimating agricultural production, considering the interplay of organic, economic, and seasonal variables, particularly amid a growing population. Predicting crop yields is crucial for farmers' planning, covering storage and marketing strategies. However, this task is complex and requires foresight. Data mining techniques emerge as a potent tool, leveraging extensive datasets to extract invaluable insights. By employing methods like Random Forest, this research offers a swift yet comprehensive examination of crop yield forecasts for specific regions. Predictive analyses like these act as a crucial asset, enabling stakeholders to make well-informed decisions grounded in expected patterns and trends.”
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