A Prediction of Crop Yield using Machine Learning Algorithm

Abstract

Fertilizer value features a positive practical significance for guiding agricultural production and notifies the change in market rate of fertilizer to the farmer. This research work proposes an information analysis technology to update the speed change through notification. The notifications are sent immediately, when the speed of the fertilizers modified within the market. So, the standard of the fertilizers is identified by using ranking process. By this process, the speed of the inferiority and high-quality fertilizer is additionally notified. The usage of ensemble of classifiers leverages a stronger decision on prediction because of the usage of multiple classifiers.