Abstract
Among worldwide, agriculture has the major responsibility for improving the economic contribution of the nation. However, still most agricultural fieldsare underdeveloped due to the lack of deployment of ecosystem control technologies. Due to theseproblems, the crop production is not improved which affects the agriculture economy. Hence a development of agricultural productivity is enhanced based on the plant yield prediction. To prevent this problem, Agricultural sectors have to predict the crop from given dataset using machine learning techniques. The examination of dataset by coordinated ML techniques. A comparative study between machine learning algorithms had been carried out in order to determine which algorithm is the most accurate in predicting the best crop .In this we are going to predict the yield if a specific crop is selected else we will predict the yield ofall the crops using the parameters District name, season and year. Keywords : dataset, Machine Learning- Regression methods, mean absolute error, R2- score
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