Crop Prediction Using Ensemble Learning

Most developing countries, including India, depend on agriculture as their primary source of revenue. Earlier, crop cultivation was based on farmers' prowess. There are many types of soil, each of which has its own unique properties and specialty, ensuring the proper cultivation of a particular crop. However, the changes in climate and temperature have adversely affected the yield of crops, so farmers cannot choose the correct crop to be grown based on environmental factors. Accurate crop prediction will lead to increased crop production, resulting in high revenue. Crop prediction using ensemble learning is the process of integrating various learning algorithms to make predictions. Each algorithm has its pros and cons, thereby having a certain level of accuracy, but grouping the predictions of different algorithms to make a combined prediction will improve the accuracy of the prediction.