Research on suspected culprit recognition based on Probit

In order to recognize the criminal suspects in the crowd relevant to the case by computer and improve the efficiency of solving the case, this paper presents a new method of suspected culprit recognition based on Probit model. Separation algorithm, correlation algorithm based on cluster and the parameters named significance level in Probit model are adopted to find the important attributes of the culprit, and then, by training the data just including the important attributes, the crime risk evaluation model could be achieved. The experimental results show that average accuracy of model-recognizing-culprit is 90.5% and the average recall is 92.7%.