Prediction of University Students' Scholarship Grade for Excellent Students Based on Machine Learning

In all stages of school education, scholarship is one of the means to encourage students to continue to be proactive. Therefore, student scholarship evaluation is something that relevant teachers often encounter. In order to help these teachers evaluate students' scholarships, this paper proposes a machine learning-based method for predicting students' scholarship grades. In the first stage, the data of student scholarship evaluation data is first obtained; the second step is to preprocess the relevant data; the third step is preliminary analysis and visual display of the data; the fourth step uses machine learning algorithms to deeply mine the information and save the best model; the fifth step uses the aforementioned model to predict the scholarship level of the new data sample. After a lot of training and experiments, good scoring results have been achieved on the training set, verification set, and test set, which can facilitate the work of relevant teachers.