There are a few general methods that help in improving the accuracy of the forecasting model. In this section, we will have a brief discussion about these methods.
The widely used method is to split the dataset into training and testing. Build the forecasting model using the training dataset and test for the accuracy using the testing dataset. Rebuild the forecasting model by tweaking the parameters until the error is minimal.
The other method is to combine multiple algorithms and compute the weighted average in order to arrive at the final prediction.
As the seasonality and trend have a high influence on the forecasting model, it is better to keep updating the forecasting model on a frequent basis.
