network, the system will suggest the preliminary classifications that will be sent on to the next and final phase. By the end of the neural network phase, all of the input data will have been analyzed, grouped, and classified into patterns that will become the basis for which the final results depend on. Heuristics System Phase The heuristics system phase is the final phase of the CSSCP application and is the stage at which the output data is refined. During this phase, the preliminary classifications that were developed in the previous phase are enhanced in order to improve classifications or to eliminate deficiencies. In CSSCP, heuristics are used for two main purposes: Adding records to a class Extracting records from a class CSSCP uses heuristics to add records to a class that have been left out by the neural network. In CSSCP in particular, crimes that occur before midnight and after midnight would not be grouped together during the neural network phase regardless of how many similarities exists between them. The use of heuristics corrects this problem by adding an appropriate group for both crimes to be grouped together. CSSCP also uses heuristics to extract or remove records from a class in two ways. One way is in instances where the neural network has grouped two or more specific crimes together that cannot be related to each other. The second way is in instances when classifications have been created that are irrelevant to the user; such as when a group is created to compare characteristics of multiple criminals involved in the same crime as opposed to a group that compares the characteristics of the crime itself. Applications The first use of CSSCP was during a trial study in which statistics from three years of armed robbery cases were analyzed. Professor Muscarello decided to demonstrate with armed robbery cases not only because they were some of the most frequent cases dealt with by police, but also because they tend to demonstrate common patterns that would highlight the abilities of CSSCP. During the trial, CSSCP demonstrated how it could correctly classify patterns at a much higher rate than the suggested one percent that a Rand Corporation study reported as the common rate. Because of CSSCP's success during the trial studies, the Chicago Police Department decided to conduct live trials of CSSCP on their networks in 2006. However, due to upper management changes