Prediction of crop production using adaboost regression method

Territorial evaluations or forecast of yield creation is basic for some applications, for example, agrarian grounds administration, nourishment security cautioning framework, sustenance exchange strategy. Machine learning has risen with enormous information advancements and superior processing to make new open doors for information escalated science in the multi-disciplinary agricultural space. In this paper, we have applied and build a crop production prediction model using Decision Tree Classification and AdaBoost Regression Method. We have used the Indian Agriculture dataset. Performance analysis was done using R-squared Score.