Social Security Event Prediction Based on Machine Learning

In the construction and development of modern society, prediction, as an effective technology to evaluate the development trend and future state of things, can scientifically deal with the problems existing in traditional technical methods, and provide the basic guarantee for social economy and people’s security. At present, domestic and foreign scholars have put forward a number of forecasting methods in the comprehensive study, which are mainly divided into quantitative forecasting and qualitative forecasting. Although China has begun to pay attention to social risk forecasting in the past construction, the technical means mastered in practice cannot reach the level of developed countries under the influence of factors such as theoretical knowledge and technical level. Therefore, after understanding the current development status of social security event prediction in China, this paper mainly explores the application effect of credit risk prediction according to the machine learning model structure and social risk prediction method. The final experimental results prove that the construction of social risk prediction model based on machine learning algorithm can not only grasp more valuable data information, but also effectively prevent various events that endanger social security.