Linear Regression Approach to Predict Crop Yield

Abstract

The agriculture plays a very big and important role for the country’s growth. The agriculture science system facing lots of problems from the environmental change. Machinelearning (ML) is the best approach to overcome the problems by building the good and effective solutions. Crop yield prediction include prediction of yield for the crop by analyzing the existing data by considering several parameters like weather, soil, water and temperature etc. This project addresses and defines the predicting yield of the crop based on the previous year’s data using Linear Regression algorithm. The approach of this project is to solve the problem of cost loss. Real agricultural data is used for making the models and the models tested with the samples. The prediction model will help the end users (farmers) to predict the crop yield before cultivation of the crop onto the agricultural field. To predict the accurate results Linear Regression machine algorithm is used. The presence of large dataset will help to improve the decision making model.