The paper also deals with this problem by introducing a validation index of dynamic partitions of crime events that relates the optimal number of clusters with the foreseeability of time series by means of non-linear analysis. One of the main drawbacks of clustering is the difficulty of defining the optimal number of clusters. The size of this set corresponds to the number of clusters multiplied by the number of parameters per cluster. Cluster dynamics are captured as a set of time series.
In this approach, clusters of criminal events are parametrized according to simple geometric prototypes. This chapter presents an approach to forecast criminal patterns that combines the time series from clustering method with a computational intelligence-based prediction.
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