Crop Prediction Using ML
Aishwaryendra Narayan, Shashwat Singh, Anushthan Pandey, Aman Singh
Crop yield prediction, Lasso, Kernel Ridge, ENet, Stacked Regression, Machine Learning (ML).
The significance of agriculture in India's economy is widely acknowledged. This research paper focuses on predicting crop yields across the country, covering a wide range of crops. What distinguishes this study is its unique capability to forecast agricultural production for any chosen year, using easily understandable factors such as state, district, season, and area. To accomplish this, the article employs various regression techniques, including the notable Kernel Ridge, Lasso, and ENet algorithms. These advanced statistical methods serve as the foundation of the paper's prediction methodology, facilitating accurate estimations of crop output.
Article Details
Unique Paper ID: 160133

Publication Volume & Issue: Volume 9, Issue 12

Page(s): 1353 - 1356
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