Multi-knowledge extraction from violent crime datasets using swarm rough algorithm

This paper presents a swarm rough approach to analyze the combination factors of violent crime. The approach discovers the feature combinations in an efficient way to observe the change of rough set positive region as the fuzzy swarm proceed throughout the search space. We evaluated the performance of our approach using the violent factor datasets and the corresponding computational experiments are discussed. Empirical results indicate that our approach is ideal for all the considered problems and the fuzzy swarm optimization technique outperforms dynamic reducts (DR) approache by obtaining multiple reductions for the combination factor datasets.