| The algorithms APS 3.0 uses for Time Series Prediction
allow not only the creation of models but also the use of these models to make predictions. APS 3.0 allows you to make two kinds of predictions: one for testing past known events and another for making predictions about the future or about unknown behavior. In both cases, though, predictions are made recursively, by evaluating the forecast at t+1, then using it to forecast t+2, and so on. You must choose either one of these methods while loading your time series data, as this imposes some constraints on the restructuring of the time series for training. Namely, n testing records (the n last ones) are saved for testing and sometimes a small number of records from the top must be deleted. However, you can also change these parameters later in the Settings Panel -> General Settings Tab.
Thus, the first type of predictions (testing) can be used for research or pre-evaluation purposes, as it allows you to test the forecasting capabilities of your model on a set of test observations.
The second type of predictions (prediction) is used obviously to predict unknown behavior, and APS 3.0 allows you to venture into the future as far as you see fit, by setting the number of predictions you want to make and then click the Predict button.
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