Agriculture is the backbone of India. In order to support farmers in India, this research is focused on the design of various predictive models that are used to predict the yield value for a specific crop in Indian states. This research work considers Rice, Wheat, and Bajra crops in Tamil-Nadu, Rajasthan, Uttar Pradesh states respectively. The various regression models such as Linear, Multiple, C4.5 and Random Forest are considered in this work. R squared value is used to evaluate the performance of the regression models. The result of this work shows that Random Forest model is better in performance.
CITATION STYLE
Jain*, V., & V., V. (2020). Design and Implementation of Various Regression Models for Yield Prediction. International Journal of Innovative Technology and Exploring Engineering, 9(5), 1280–1284. https://doi.org/10.35940/ijitee.e2766.039520
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