fig7 as more data from the website is gathered and stored the operator preferably periodically reassesses the mathematical equations used to make the classification decisions to ensure the validity of the equations block 700 commodity statistical analysis software produces models for sets of inputs regardless of the irregularity of the inputs thus once the operator produces models using the statistical software the operator evaluates the models against another standard block 702 the other standard usually is taken to be the measure of the classification outcome at the time of the analysis for example if someone develops software to perform pattern recognition analysis on bone fragments for the purposes of species classification the pattern recognition software i e statistical models would best be evaluated against the judgments of a scholar who specializes in identifying species by looking only at bone fragments the operator who can observe many website interactions desirable and undesirable can apply two sets of model validating processes the first of these two model validation techniques is retrospective block 706 referring to fig8 the outputs of the models are evaluated by for example a domain expert using the model 39 s input data stream the domain expert evaluates multiple interactions for example hundreds or thousands of interactions upon which the models are built cataloging each one as valid or invalid block 800 the domain expert can then create a two by two classification table as follows block 802 using.