Abstract:
Rice is the most grown crop in Bangladesh. It is consumed as the main food course in Bangladesh. The price of rice makes a difference in whether people will eat or starve. To know what's going to happen in the rice market using pen and paper is a far cry as well as time-consuming. Machine Learning (ML) provides the facilities to predict the price of any products to prevent a future collapse in the market. The goal of this paper is to predict the price of rice using Machine learning approach. Data collected from the Ministry of Agriculture website, Bangladesh was used to predict the price. Several machine learning algorithms were used to make this prediction i.e. Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naïve Bayes, Decision Tree and Random Forest. All these algorithms are analyzed to find out which algorithm provides the best performance. Now, we can predict the price of rice, whether it is reasonable, low, or high based on the results achieved by the mentioned algorithms.
