An unattended ground sensor (UGS) that attempts to perform target identification without providing some corresponding estimate of confidence level is of limited utility. In this context, a confidence level is a measure of probability that the detected vehicle is of a particular target class. Many identification methods attempt to match features of a detected vehicle to each of a set of target templates. Each template is formed empirically from features collected from vehicles known to be members of the particular target class. The nontarget class is inherent in this formulation and must be addressed in providing a confidence level. Often, it is difficult to adequately characterize the nontarget class empirically by feature collection, so assumptions must be made about the nontarget class. An analyst tasked with deciding how to use the confidence level of the classifier decision should have an accurate understanding of the meaning of the confidence level given. This paper compares several definitions of confidence level by considering the assumptions that are made in each, how these assumptions affect the meaning, and giving examples of implementing them in a practical acoustic UGS.