Krishna Priya, S.R and NARANAMMAL (2024) Use of Random Forest Regression Model for Forecasting Food and Commercial Crops of India. Use of Random Forest Regression Model for Forecasting Food and Commercial Crops of India, 97: 00130. ISSN 2117-4458

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Abstract

Agriculture is the backbone of Indian Economy. Proper forecast
of food crops and cash crops are necessary for the government in policy
making decisions. The present paper aims to forecast Wheat and Sugarcane
yield using Random Forest Regression. For the development of Random
Forest models, Yield has been taken as dependent variable and variables like
Gross Cropped Area, Maximum Temperature, Minimum Temperature,
Rainfall, Nitrogen, Phosphorous Oxide, Potassium Oxide, Minimum
Support Price and Area under Irrigation are taken as independent variables
for both Wheat and Sugarcane crop. Values of R2 for Wheat and Sugarcane
is 0.995 and 0.981which indicates that the model is a good fit and other
performance measures are calculated and results are satisfactory

Item Type: Article
Divisions: PSG College of Arts and Science > Department of Management Sciences
Depositing User: Dr. B Sivakumar
Date Deposited: 12 Dec 2025 09:34
Last Modified: 12 Dec 2025 09:34
URI: https://ir.psgcas.ac.in/id/eprint/2593

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