Precise stipend of undergraduates based on multi-view and classification ensemble

Abstract

With the development of education informatization, the data-driven education reform has gradually become a research hotspot. The arrival of digital campus brings new opportunities for the higher education institutions to promote convenient and efficient precise stipend. In this paper, a model based on multi-view and classification ensemble is proposed to predict the stipend of undergraduates. Firstly, the multi-dimensional data of undergraduates is divided into two different views according to their learning performance and living behavior. Then, the multi-view learning methods are used to obtain more discriminative features, and the classification ensemble is applied to predict the stipend of undergraduates at last. The experimental results show that the proposed model based on multi-view and classification ensemble can effectively achieve the stipend prediction.