Vegetable Price Forecasting using Machine Learning Models
The SARIMA and PCA model files display seasonality of the factors which were considered for predicting the vegetable prices. Data_Sheet contains the database prepared for vegetable prices along with factors such as date,season, rainfall, avg. of prev 5 days, vegetable category, festival, arrival, inflation. Graph of All 4 years contains graphical representation from 2018 to 2021 Random Forest accuracy Predictor predicts accuracy by using RandomForestRegressor. Price prediction using Random Forest is a working predicting model for a specific date. Correlation of different factors is calculated.