Crop Prediction Using ML
Author(s):
Aishwaryendra Narayan, Shashwat Singh, Anushthan Pandey, Aman Singh
Keywords:
Crop yield prediction, Lasso, Kernel Ridge, ENet, Stacked Regression, Machine Learning (ML).
Abstract
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
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews