The Forest_Predict function uses the model generated by the Forest_Drive function to generate predictions on a response variable for a test set of data. The model can be stored in either a table or a file.
Forest_Predict outputs the
probability that each observation is in the predicted class. To
use Forest_Predict output as input to the Receiver Operating Characteristic (ROC) function,
you must first transform it to show the probability that each observation is in the positive class. One way to do this is to change the probability
to (1- current probability) when the predicted class is negative.
This function can be used with real-time applications. See AMLGenerator.