Prognosis of Yield of Crop using Machine Learning Techniques

Abstract

India is the country which is dependent on agricultural filed where the economic status entirely or partially depends on this. Selection of crops is the major phase in agricultural planning or for cultivation. But selection of crops depends on various factors such as climatic conditions, market-price, production rate etc. We can improve the agriculture production in our country by using machine learning models which is applied on different sectors of farming. With improvement in the machine learning models the ability to improve the prediction of crop yield is also high. In this paper we use techniques of advanced regression such as Kernel Ridge, Lasso, E-net and polynomial regression algorithms to detect yield and stacked regression conception to enhance the algorithms used for better prediction. This paper mainly uses squared error loss. In addition a user friendly web application is developed for better predictions.