SOYBEAN OIL PRICE PREDICTION USING MACHINE LEARNING APPROACH

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SOYBEAN OIL PRICE PREDICTION USING MACHINE LEARNING APPROACH

ABSTRACT

Uncertainty in the market is a persistent problem in Nigeria. Because of this, the cost of our standard ingredients varies greatly. It has a significant impact on the ingredient that we eat each day. Different types of oil are available in Nigeria. Soybean oil is one of them. Soybean oil is a common ingredient in meals in Nigeria. It is necessary to record the pricing of the daily-used items, but doing so manually is challenging. The ability to monitor prices for those who are below the poverty line is quite useful. In the age of artificial intelligence, we now have sophisticated gadgets that can extract information from data. Machine learning algorithms may be combined with data understanding for predictive applications. Foresight can be an effective way to reduce market volatility. In our research, we look for ways to use machine learning to predict the price of soy bean oil in the future. Our study is based on unprocessed data from Nigeria’s Ministry of Agriculture (MOA). There are various prediction techniques in machine learning. Gradient Boosting, Decision Tree Regression, Lasso Regression, Linear Regression, MLP Regression, and Random Forest methods were used to develop our solution. To determine the best accuracy, we compared performance accuracy. Every algorithm operates about symmetrically. Finding the future prices of soybean oil was our main goal.

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