The threshold option is beneficial for analyzing network models that generate an up or down prediction (for example, a financial model that is predicting percent gains and losses). A threshold value is specified and only network predictions that exceed the threshold (+ or -) are counted “Correct” or “Wrong”. “Correct” and “Wrong” is determined by the direction change of the actual target. If both the prediction and target move in the same direction (i.e. have the same sign) and the prediction exceeds the threshold, a “Correct” case would be counted. “Wrong” cases occur when the predicted direction is not correct. If the network prediction does not exceed the threshold, the case is ignored. By analyzing results of several threshold values, one can determine the point that the network model begins to yield reliable predictions. For models that do not have this type of output format, this option will not provides no useful information.