Study on Student Portrait Writing Based on EM-FCM Algorithm

With the proposal and application of digital campus, all platforms have accumulated massive education data, how to make these data resources better service teachers and students need to solve problems. To this end, this paper proposes Study on Student Portrait Side Writing Based on EM-FCM Clustering Algorithm. This method proposes five dimensional labels to describe college students' learning behavior; for the FCM clustering algorithm, it is easy to fall into local optimal issues, and the EM-FCM algorithm is proposed and labeled with label clusters. Get a typical student portrait. The simulation results show that the article proposes that the student label meets the students' characteristics, and the algorithms can be effectively classified, and the basic FCM algorithm is faster, and the student portrait is closer to the actual.