Prediction of tariff rate machine learning project Tariff is a list of expenses that incur while transporting the goods from one distance to another distance. Tariff is also dependent on seasonal and non-seasonal factors also. This project is aimed at predicting the tariff rates for truck load by using the different machine learning algorithms like lasso regression, elastic net regression, ridge regression and linear regression. Tariff is a combination of lot of things and tariff rate is dependent on some of the factors like Year, Road, Seasonal Impact, Fuel Cost, Distance, Weight, Toll charge, Demand, labour cost, travel expenses etc. Using some of these factors and by employing the above-mentioned machine learning regression algorithms we will be trying to predict the tariff rates on the trucks. By doing this we can help the industries to estimate the tariff rates so that they can take the necessary actions and they can make their business run in profitable way. This model helps small- and large-scale firms to control and manage the cost on transport
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