Parameterize the model using actual data. Transactions are used to determine
the probabilities to be attached at each process and control point that relate the
processing to the data available in the transactions. Using these parameters, the
model is trained so that outliers and anomalies can be detected and dealt with on
a day-to-day basis.
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