Crop Yield Estimation in India Using Machine Learning

Agriculture in India is significant economic support. The population growth is the major challenge for food security. The population growth makes a rise in demand which requires farmers to produce more from the same agriculture land in respect to increase the supply. Technology can help farmers to produce more with the help of crop yield prediction. The main aim of this paper is to predict crop yield using area, yield, production, and area under irrigation. Four machine learning techniques Decision Tree, Linear Regression, Lasso regression, and Ridge Regression have been applied to estimate the crop yield. Cross validations methods, for validation, mean absolute error, mean squared error, and root mean squared error, were used to validate. The Decision tree outperforms other machine learning techniques.