Crop price prediction using supervised machine learning algorithms

Abstract Our target is focused largely on agriculture. In agriculture, farmers play the most important role. When price falls after harvest, face immense losses. A country’s GDP affected by fluctuations of agricultural products. Crop estimation and evaluation are done to take an intelligent decision before farming a specific type crop. Predicting crop will help in taking better decisions which results minimizing loss managing risk fluctuations. this paper, we predicted different crops analyzing previous rainfall WPI data. We used tree regressor (Supervised machine learning algorithm) analyze data predict for latest estimate twelve months come.