Predictive Analysis for calculation of crop yield using Datamining and Machine Learning

India is an agricultural country. The annual crop yield is largely dependent on a number of climatic and geographical conditions that include temperature, pressure, location, and humidity. Completely relying on the traditional system to predict the crop yield is not a viable option due to the uncertainties in these conditions. Thus, the main aim of this research is to implement data mining and machine learning algorithms to create a model that accurately predicts crop yield. For this, the data is acquired, processed and feature scaling is used. Then the machine learning algorithm XGBoost is implemented. The accuracy obtained was as high as 99.99706%.