Research on Undergraduate Academic Prediction Model Based on Deep Learning

摘要

Academic prediction is an important management means to strengthen the construction of study style and improve the quality of talent training in Colleges and universities. In view of the current colleges and universities lack of scientific and effective methods in the undergraduate academic prediction, based on deep learning of undergraduate academic prediction model, the model mainly includes the construction of feature reconstruction and prediction model of the two modules, the feature extraction module, including the selection of students, characteristics of format conversion and dimension recombination; model the convolutional neural network the characteristics of the input after the reorganization of the improved training and validation, the model parameters were optimized, and then use the model to forecast. Taking the data from 2007 to 2010 students in a university in Beijing as training set, the model is trained, and 2011 level students are selected as the validation set to optimize the model parameters, and the 2012 level student data set is used to evaluate the model. The results show that the undergraduate academic prediction model based on CNN neural network has higher prediction accuracy. And then help colleges and universities to optimize the teaching management methods and improve the quality of teaching.