The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by Group of answer choices using the current value to estimate how well the model generates previous values correctly. determining how well a particular forecasting method is able to reproduce the time series data that are already available. adjusting the scale of the data. predicting the future values and wait for a pre-defined time period to examine how accurate the predictions were.