Design And Application On Mental Health Problems For Undergradute

With the rapid development of network technology, we can obtain more and more data conveniently. The huge volumes of data ought to be mined valuable rules and links between the frequent data, which can offer decision support for decision-maker, instead of restricting their applications to ordinary queries and statistic analysis methods. At present, the social environment that the university students faces has changed greatly, and the students own the new characteristics different from the whole ages before in many subjects,such as their study initiative, interests, academic record, the increasing gap between rich and poor and the pressure of employment competition. What’s more, the factors that induced mental health problems have emerged more complicated characteristics. Therefore, it is necessary to go into more detail on the mental health problems by modern information technique.This paper analyses and summarizes the current research of data mining for the mental health problems by collecting and reviewing the related literature both domestic and abroad, and on this basic we present a new approach. The major innovation is that we classify the mental health problems to data mining problems of imbalanced data sets and use the anomaly detection techniques to solve the problem. In addition, various data and association analysis technology are synthesized to dig deeper and analysis the origin cause of the mental health problems, which can make the analytical results more reasonable and effective.After analyzing some fundamentals in detail, such as data mining, data warehouse, clustering analysis methods, outlier mining methods and association rules algorithm, we promote outlier data mining algorithms based on clustering to inspect and deal with outlier data effectively on the data about the mental health problems of university students. With this, the students of the potential mental health problems can be identified. As to the origin cause, we forecast test data by the Apriori algorithm and the main step is to analyze the inner relation between the mental health problems and properties. The origin cause based on real data can provide a reliable basis for the psychology teaching staff, which can also improve the efficiency and effectiveness of school mental health education.