Research On The Supervision Of Stock Market Based On The Protection The Interests Of Medium And Small Investors

With the rapid development of the mobile network,the clients' demand for Internet access has been dramatically growing both on mobile terminals as well as on the PC/wap ends.Gradually,mobile phones have playing a key role as one of the essentials in people's lives and somehow become a new 'organ' of our bodies.Simultaneously,with the applications on mobile ends market being increasingly popular,in order to obtain more of the users' resources,various types of APPs launched fierce competition.On one hand,the situations in a certain rate have reversely propelled the prosper of the market,enriching the choices of customers;And at the same time,it also increased the probability of user churn.Users are the most valuable resources for Internet enterprises,with which they are able to maintain the flow and the vitality.Therefore,preventing users from losing is a critical and first-line issue that all the participants must consider.To stay away from being eliminated in the competition,it is necessary not only to continuously iteratively preserve the appeal of the product to the users,but also to comprehend the user's preferences in depth and to discover the implied causality between the user behavior and the loss itself.Meanwhile,facts are that the costs for new users soliciting is high,yet the loss characteristics are not evenly observative,and the loss rate is still high.If accurate predictions on users' behavior are available,and targeted retention strategies are feasibly designed for users with different probability of loss to keep users' retention.it could have been profoundly significant for enterprises.Fortunately,model prediction in data mining can well meet the demand.In this paper,I studied the churn prediction model of the socialization in strangers' domain based on data mining,introducing the research progresses and status quo of user churn.To explore the relationship between different attributes and different behaviors and the user churn,I applied the exploratory data methods,and compared the Decision Tree model and the Random Forest model as well as the Logistic Regression model and XGBoost model,simulating the performance of the four kinds of prediction models in the area of user loss.And finally the XGBoost was selected as a primary method to present the output featured important metrics and the probability of loss of all users during the forecast period,which provided decision-making basis for retention of the users.