Abstract
India is a country where agriculture and agricultural industries provide the majority of the country’s income and economy. Farmers have traditionally had a difficult time predicting prices for agricultural crops. Farmers are currently losing a lot of money owing to price fluctuations caused by climatic change and other price influencing factors. Farmers are unable to obtain the price they desire for their produce. The goal of this project is to develop a decision-making assistance model for agricultural product price prediction. This technique can be used as a guide when deciding what a farmer should plant, taking into account factors such as annual rainfall, WPI, and so forth. The system provides a 12-month forecast in detail. Decision tree regression, a machine learning regression technique, is the methodology we employ in the system. KEY WORDS: Price Prediction, Machine Learning, WPI, Decision Tree Regression.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
