Comparative Analysis of Machine Learning Techniques for Crop Yield Prediction

Abstract: In agricultural field the crop yield prediction is significant and also a challenging task. Earlier, yield prediction was performed by considering farmer's experience on particular field and crop. This always requires involvement of farmer in prediction of crop yield which is not possible always. To overcome this challenge automated way to predict the yield of crop is proposed. In this work comparative analysis of crop yield prediction model using Machine learning techniques for the selected region i.e. district of Tamil Nadu in India. The machine learning algorithms like K-Nearest Neighbour, Decision Tree (Regression), Support Vector Regression were implemented and the performance of crop prediction model was analysed. The experimental analysis suggested that the performance for Support Vector Regression is better than K-Nearest Neighbour, Decision Tree, Support Vector Regression models.

Keywords: Machine Learning, K-Nearest Neighbour, Decision Tree, Support Vector Regression, Crop Yield Prediction.