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Using Decision Trees to Predict Crime Reporting
Abstract
Crime reports are used to find criminals, prevent further violations, identify problems causing crimes and allocate government resources. Unfortunately, many crimes go unreported. The National Crime Victimization Survey (NCVS) comprises data about incidents, victims, suspects and if the incident was reported or not. Current research using the NCVS is limited to statistical techniques resulting in a limited ‘view’ of the data. Our goal is to use decision trees to predict when crime is reported or not. We compare decision trees that are built based on domain knowledge with those created with three variable selection methods. We conclude that using decision trees leads to the discovery of several new variables to research further.
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