使用各种机器学习技术预测商品价格

S. Rani, Sandeep Kumar, V. T, Arpit Jain, A. Swathi, R. M
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引用次数: 2

摘要

这一进步极大地帮助了印度农村地区的人们使用通信技术。人们可以使用互联网或智能手机获取信息。在印度,农业是大多数人的主要工作。然而,农民仍然不知道农业技术的变化。印度农民有一个大问题:他们没有得到合理的农作物价格。另一个大问题是农民没有得到足够的钱,或者他们种植的东西没有更好的价格。他们不知道市场趋势,也不知道市场之间发生了什么。因为他们不知道未来的价格,他们无法决定何时何地出售他们的作物。在本文中,我们提出了一个估算商品价格的模型。通过使用线性回归、随机森林和决策树等技术。该模型在标准数据库上执行,准确率达到95%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Commodities Price Prediction using Various ML Techniques
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%.
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