1. A non-transitory computer readable medium for estimating a confidence level of a classification assignment, the non-transitory computer readable medium having instructions configured to cause a processor of a computer to: create a data model having a plurality of classes of records, the data model being based on a set of pre-classified records; assign one of said classes to a new record; obtain a qualitative confidence level for the assignment of said class; obtain a quantitative confidence level for the assignment of said class; and combine the qualitative confidence level and the quantitative confidence level, wherein the quantitative confidence level is obtained by finding a ratio of the probability of said class to a second most likely class, finding a ratio of a complement probability of said second most likely class to a complement probability of said class, and using matchfactors to generate a scaled ratio.