Commodities Price Prediction using Various ML Techniques
Shilpa Rani, Sandeep Kumar, Venkata Subbamma. T, Arpit Jain, A. Swathi, Ramakrishna Kumar
Abstract
The progress immensely helped people in rural India with communication technology. People can use the internet or a smart phone to get information. In India, agriculture is the primary job for most people. However, farmers still do not know about the changes in technology in agriculture. Farmers in India have a big problem: they do not get a reasonable crop price. Another big problem is that farmers do not get enough money or a better price for the things they grow. They do not know the market trend or what is happening between markets. Because they do not know what the price will be in the future, they cannot decide when and where to sell their crops. In this article, we proposed a model for estimating commodity prices. By using techniques like Linear Regression, Random Forest, and Decision Trees. The model performed on standard database and achieved an accuracy score of more than 95%.