Modeling the adaptive immune system: predictions and simulations

Lundegaard, Claus; Lund, Ole; Kesmir, Can; Brunak, Søren; Nielsen, Morten

As an evaluation of the general quality of a prediction method a measure describing this quality is needed. However, no single measure can capture all qualities of a prediction, and not all types of data and predictions can be reasonably described by the same measure. So to be able to compare different systems, it is often needed to present several measures of quality. Most measures need the data to be classified into two groups, i.e. positives and negatives. The number of classified (experimentally measured) positives is often designated as actual positives (AP), and the number of negatives, actual negatives (AN), the number of predicted positives (PP), predicted negatives (PN), truly predicted positives (TP), falsely predicted positives (FP), truly predicted negatives (TN), and falsely predicted negatives (FN). Some of the most often used measures are briefly described here. The equations for the mentioned measures are given at the end of the section.