ESTIMATION OF PRICES IN AGRICULTYRAL COMMODITY USING MACHINE LEARNING
CH.Bhanu Kumar , Sri.M.Anil
M.Tech student, SANKETIKA VIDYA PARISHAD ENGINEERING COLLEGE
India is a country where agriculture and agricultural industries provide the majority of the countryâ€™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.
Keywords: Price Prediction, Machine Learning, WPI, Decision Tree Regression.
Journal Name :
EPRA International Journal of Research & Development (IJRD)
Published on : 2021-09-04