AjasaHameed/Machine-Learning-Prediction-Symbolic-Regression

In this case, a novel approach: symbolic regression is used to predicts the prices of Nigeria common food prices. This study model the prices of food items in Nigeria focusing on the most commonly consumed items such as rice, beans and garri in two regions; South West and North Central of Nigeria. The study deployed machine learning techniques such as random forest, decision tree, neural network and a novel method, Symbolic regression. Accross the regions and for each food item, the new model outperformed the coventional machine learning techniques in predicting the prices using exchange rate, inflation rate and crude oil prices in Nigeria. One of the strength of sybolic regression is that it ensures transparency unlike to other ML models that are black box.