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Ascertaining the Fluctuation of Rice Price in Bangladesh Using Machine Learning Approach

机译:使用机器学习方法确定孟加拉国大米价格的波动

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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.
机译:水稻是孟加拉国种植最多的作物。它被消费为孟加拉国的主要食物。大米的价格会影响人们吃还是饿。要知道使用笔和纸在大米市场上会发生什么,既是费时又费力的事情。机器学习(ML)提供了预测任何产品价格的功能,以防止未来市场崩溃。本文的目的是使用机器学习方法预测大米的价格。从孟加拉国农业部网站收集的数据用于预测价格。使用了几种机器学习算法来进行此预测,即支持向量机(SVM),K最近邻(KNN),朴素贝叶斯,决策树和随机森林。对所有这些算法进行了分析,以找出哪种算法可提供最佳性能。现在,基于上述算法所获得的结果,我们可以预测大米的价格,无论是合理的,低的还是高的。

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